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Andrea Vedaldi
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2020 – today
- 2024
- [j19]Subhabrata Choudhury
, Iro Laina, Christian Rupprecht, Andrea Vedaldi:
The Curious Layperson: Fine-Grained Image Recognition Without Expert Labels. Int. J. Comput. Vis. 132(2): 537-554 (2024) - [c185]Tomas Jakab, Ruining Li, Shangzhe Wu, Christian Rupprecht, Andrea Vedaldi:
Farm3D: Learning Articulated 3D Animals by Distilling 2D Diffusion. 3DV 2024: 852-861 - [c184]Luke Melas-Kyriazi, Iro Laina, Christian Rupprecht, Natalia Neverova, Andrea Vedaldi, Oran Gafni, Filippos Kokkinos:
IM-3D: Iterative Multiview Diffusion and Reconstruction for High-Quality 3D Generation. ICML 2024 - [c183]Minghao Chen, Iro Laina, Andrea Vedaldi:
Training-Free Layout Control with Cross-Attention Guidance. WACV 2024: 5331-5341 - [i171]Zizhang Li, Dor Litvak, Ruining Li, Yunzhi Zhang, Tomas Jakab, Christian Rupprecht, Shangzhe Wu, Andrea Vedaldi, Jiajun Wu:
Learning the 3D Fauna of the Web. CoRR abs/2401.02400 (2024) - [i170]Luke Melas-Kyriazi, Iro Laina, Christian Rupprecht, Natalia Neverova, Andrea Vedaldi, Oran Gafni, Filippos Kokkinos:
IM-3D: Iterative Multiview Diffusion and Reconstruction for High-Quality 3D Generation. CoRR abs/2402.08682 (2024) - [i169]Abdullah Hamdi, Luke Melas-Kyriazi, Guocheng Qian, Jinjie Mai, Ruoshi Liu, Carl Vondrick, Bernard Ghanem, Andrea Vedaldi:
GES: Generalized Exponential Splatting for Efficient Radiance Field Rendering. CoRR abs/2402.10128 (2024) - [i168]Yash Bhalgat, Iro Laina, João F. Henriques, Andrew Zisserman, Andrea Vedaldi:
N2F2: Hierarchical Scene Understanding with Nested Neural Feature Fields. CoRR abs/2403.10997 (2024) - [i167]Ruining Li, Chuanxia Zheng, Christian Rupprecht, Andrea Vedaldi:
DragAPart: Learning a Part-Level Motion Prior for Articulated Objects. CoRR abs/2403.15382 (2024) - [i166]Minghao Chen, Iro Laina, Andrea Vedaldi:
DGE: Direct Gaussian 3D Editing by Consistent Multi-view Editing. CoRR abs/2404.18929 (2024) - [i165]Paul Engstler, Andrea Vedaldi, Iro Laina, Christian Rupprecht:
Invisible Stitch: Generating Smooth 3D Scenes with Depth Inpainting. CoRR abs/2404.19758 (2024) - [i164]Ang Cao, Justin Johnson, Andrea Vedaldi, David Novotný:
Lightplane: Highly-Scalable Components for Neural 3D Fields. CoRR abs/2404.19760 (2024) - [i163]Stanislaw Szymanowicz, Eldar Insafutdinov, Chuanxia Zheng, Dylan Campbell, João F. Henriques, Christian Rupprecht, Andrea Vedaldi:
Flash3D: Feed-Forward Generalisable 3D Scene Reconstruction from a Single Image. CoRR abs/2406.04343 (2024) - [i162]Raphael Bensadoun, Yanir Kleiman, Idan Azuri, Omri Harosh, Andrea Vedaldi, Natalia Neverova, Oran Gafni:
Meta 3D TextureGen: Fast and Consistent Texture Generation for 3D Objects. CoRR abs/2407.02430 (2024) - [i161]Yawar Siddiqui, Tom Monnier, Filippos Kokkinos, Mahendra Kariya, Yanir Kleiman, Emilien Garreau, Oran Gafni, Natalia Neverova, Andrea Vedaldi, Roman Shapovalov, David Novotný:
Meta 3D AssetGen: Text-to-Mesh Generation with High-Quality Geometry, Texture, and PBR Materials. CoRR abs/2407.02445 (2024) - [i160]Raphael Bensadoun, Tom Monnier, Yanir Kleiman, Filippos Kokkinos, Yawar Siddiqui, Mahendra Kariya, Omri Harosh, Roman Shapovalov, Benjamin Graham, Emilien Garreau, Animesh Karnewar, Ang Cao, Idan Azuri, Iurii Makarov, Eric-Tuan Le, Antoine Toisoul, David Novotný, Oran Gafni, Natalia Neverova, Andrea Vedaldi:
Meta 3D Gen. CoRR abs/2407.02599 (2024) - [i159]Aleksandar Shtedritski, Christian Rupprecht, Andrea Vedaldi:
SHIC: Shape-Image Correspondences with no Keypoint Supervision. CoRR abs/2407.18907 (2024) - 2023
- [j18]Shangzhe Wu
, Tomas Jakab, Christian Rupprecht, Andrea Vedaldi:
DOVE: Learning Deformable 3D Objects by Watching Videos. Int. J. Comput. Vis. 131(10): 2623-2634 (2023) - [j17]Shangzhe Wu
, Christian Rupprecht
, Andrea Vedaldi
:
Unsupervised Learning of Probably Symmetric Deformable 3D Objects From Images in the Wild (Invited Paper). IEEE Trans. Pattern Anal. Mach. Intell. 45(4): 5268-5281 (2023) - [c182]Samarth Sinha, Roman Shapovalov, Jeremy Reizenstein, Ignacio Rocco, Natalia Neverova, Andrea Vedaldi, David Novotný:
Common Pets in 3D: Dynamic New-View Synthesis of Real-Life Deformable Categories. CVPR 2023: 4881-4891 - [c181]Changan Chen, Alexander Richard, Roman Shapovalov, Vamsi Krishna Ithapu, Natalia Neverova, Kristen Grauman, Andrea Vedaldi:
Novel-View Acoustic Synthesis. CVPR 2023: 6409-6419 - [c180]Luke Melas-Kyriazi, Iro Laina, Christian Rupprecht, Andrea Vedaldi:
RealFusion 360° Reconstruction of Any Object from a Single Image. CVPR 2023: 8446-8455 - [c179]Shangzhe Wu, Ruining Li, Tomas Jakab, Christian Rupprecht, Andrea Vedaldi:
MagicPony: Learning Articulated 3D Animals in the Wild. CVPR 2023: 8792-8802 - [c178]Luke Melas-Kyriazi, Christian Rupprecht, Andrea Vedaldi:
PC2: Projection-Conditioned Point Cloud Diffusion for Single-Image 3D Reconstruction. CVPR 2023: 12923-12932 - [c177]Nikita Karaev, Ignacio Rocco, Benjamin Graham, Natalia Neverova, Andrea Vedaldi, Christian Rupprecht:
DynamicStereo: Consistent Dynamic Depth from Stereo Videos. CVPR 2023: 13229-13239 - [c176]Animesh Karnewar, Andrea Vedaldi, David Novotný, Niloy J. Mitra:
HOLODIFFUSION: Training a 3D Diffusion Model Using 2D Images. CVPR 2023: 18423-18433 - [c175]Yaoyao Liu, Bernt Schiele, Andrea Vedaldi, Christian Rupprecht:
Continual Detection Transformer for Incremental Object Detection. CVPR 2023: 23799-23808 - [c174]Stanislaw Szymanowicz, Christian Rupprecht, Andrea Vedaldi:
Viewset Diffusion: (0-)Image-Conditioned 3D Generative Models from 2D Data. ICCV 2023: 8829-8839 - [c173]Aleksandar Shtedritski, Christian Rupprecht, Andrea Vedaldi:
What does CLIP know about a red circle? Visual prompt engineering for VLMs. ICCV 2023: 11953-11963 - [c172]Roman Shapovalov, Yanir Kleiman, Ignacio Rocco, David Novotný, Andrea Vedaldi, Changan Chen, Filippos Kokkinos, Benjamin Graham, Natalia Neverova:
Replay: Multi-modal Multi-view Acted Videos for Casual Holography. ICCV 2023: 20281-20291 - [c171]Chuanxia Zheng, Andrea Vedaldi:
Online Clustered Codebook. ICCV 2023: 22741-22750 - [c170]Animesh Karnewar, Niloy J. Mitra, Andrea Vedaldi, David Novotný:
HoloFusion: Towards Photo-realistic 3D Generative Modeling. ICCV 2023: 22919-22928 - [c169]Aleksandar Shtedritski, Andrea Vedaldi, Christian Rupprecht:
Learning Universal Semantic Correspondences with No Supervision and Automatic Data Curation. ICCV (Workshops) 2023: 933-943 - [c168]Uriel Singer, Shelly Sheynin, Adam Polyak, Oron Ashual, Iurii Makarov, Filippos Kokkinos, Naman Goyal, Andrea Vedaldi, Devi Parikh, Justin Johnson, Yaniv Taigman:
Text-To-4D Dynamic Scene Generation. ICML 2023: 31915-31929 - [c167]Yash Bhalgat, Iro Laina, João F. Henriques, Andrea Vedaldi, Andrew Zisserman:
Contrastive Lift: 3D Object Instance Segmentation by Slow-Fast Contrastive Fusion. NeurIPS 2023 - [c166]Vadim Tschernezki, Ahmad Darkhalil, Zhifan Zhu, David Fouhey, Iro Laina, Diane Larlus, Dima Damen, Andrea Vedaldi:
EPIC Fields: Marrying 3D Geometry and Video Understanding. NeurIPS 2023 - [c165]Sagar Vaze, Andrea Vedaldi, Andrew Zisserman:
No Representation Rules Them All in Category Discovery. NeurIPS 2023 - [c164]Mohamed El Banani, Ignacio Rocco, David Novotný, Andrea Vedaldi, Natalia Neverova, Justin Johnson, Benjamin Graham:
Self-supervised Correspondence Estimation via Multiview Registration. WACV 2023: 1216-1225 - [i158]Changan Chen, Alexander Richard, Roman Shapovalov, Vamsi Krishna Ithapu, Natalia Neverova, Kristen Grauman, Andrea Vedaldi:
Novel-View Acoustic Synthesis. CoRR abs/2301.08730 (2023) - [i157]Uriel Singer, Shelly Sheynin, Adam Polyak, Oron Ashual, Iurii Makarov, Filippos Kokkinos, Naman Goyal, Andrea Vedaldi, Devi Parikh, Justin Johnson, Yaniv Taigman:
Text-To-4D Dynamic Scene Generation. CoRR abs/2301.11280 (2023) - [i156]Luke Melas-Kyriazi, Christian Rupprecht, Iro Laina, Andrea Vedaldi:
RealFusion: 360° Reconstruction of Any Object from a Single Image. CoRR abs/2302.10663 (2023) - [i155]Luke Melas-Kyriazi, Christian Rupprecht, Andrea Vedaldi:
PC2: Projection-Conditioned Point Cloud Diffusion for Single-Image 3D Reconstruction. CoRR abs/2302.10668 (2023) - [i154]Ignacio Rocco, Iurii Makarov, Filippos Kokkinos, David Novotný, Benjamin Graham, Natalia Neverova, Andrea Vedaldi:
Real-time volumetric rendering of dynamic humans. CoRR abs/2303.11898 (2023) - [i153]Animesh Karnewar, Andrea Vedaldi, David Novotný, Niloy J. Mitra:
HOLODIFFUSION: Training a 3D Diffusion Model using 2D Images. CoRR abs/2303.16509 (2023) - [i152]Yaoyao Liu, Bernt Schiele
, Andrea Vedaldi, Christian Rupprecht:
Continual Detection Transformer for Incremental Object Detection. CoRR abs/2304.03110 (2023) - [i151]Minghao Chen, Iro Laina, Andrea Vedaldi:
Training-Free Layout Control with Cross-Attention Guidance. CoRR abs/2304.03373 (2023) - [i150]Aleksandar Shtedritski, Christian Rupprecht, Andrea Vedaldi:
What does CLIP know about a red circle? Visual prompt engineering for VLMs. CoRR abs/2304.06712 (2023) - [i149]Tomas Jakab, Ruining Li, Shangzhe Wu, Christian Rupprecht, Andrea Vedaldi:
Farm3D: Learning Articulated 3D Animals by Distilling 2D Diffusion. CoRR abs/2304.10535 (2023) - [i148]Nikita Karaev, Ignacio Rocco, Benjamin Graham, Natalia Neverova, Andrea Vedaldi, Christian Rupprecht:
DynamicStereo: Consistent Dynamic Depth from Stereo Videos. CoRR abs/2305.02296 (2023) - [i147]Yash Bhalgat, Iro Laina, João F. Henriques, Andrew Zisserman, Andrea Vedaldi:
Contrastive Lift: 3D Object Instance Segmentation by Slow-Fast Contrastive Fusion. CoRR abs/2306.04633 (2023) - [i146]Stanislaw Szymanowicz, Christian Rupprecht, Andrea Vedaldi:
Viewset Diffusion: (0-)Image-Conditioned 3D Generative Models from 2D Data. CoRR abs/2306.07881 (2023) - [i145]Vadim Tschernezki, Ahmad Darkhalil, Zhifan Zhu, David Fouhey, Iro Laina, Diane Larlus, Dima Damen, Andrea Vedaldi:
EPIC Fields: Marrying 3D Geometry and Video Understanding. CoRR abs/2306.08731 (2023) - [i144]Laurynas Karazija, Iro Laina, Andrea Vedaldi, Christian Rupprecht:
Diffusion Models for Zero-Shot Open-Vocabulary Segmentation. CoRR abs/2306.09316 (2023) - [i143]Nikita Karaev, Ignacio Rocco, Benjamin Graham, Natalia Neverova, Andrea Vedaldi, Christian Rupprecht:
CoTracker: It is Better to Track Together. CoRR abs/2307.07635 (2023) - [i142]Roman Shapovalov, Yanir Kleiman, Ignacio Rocco, David Novotný, Andrea Vedaldi, Changan Chen, Filippos Kokkinos, Benjamin Graham, Natalia Neverova:
Replay: Multi-modal Multi-view Acted Videos for Casual Holography. CoRR abs/2307.12067 (2023) - [i141]Chuanxia Zheng, Andrea Vedaldi:
Online Clustered Codebook. CoRR abs/2307.15139 (2023) - [i140]Animesh Karnewar, Niloy J. Mitra, Andrea Vedaldi, David Novotný:
HoloFusion: Towards Photo-realistic 3D Generative Modeling. CoRR abs/2308.14244 (2023) - [i139]Sagar Vaze, Andrea Vedaldi, Andrew Zisserman:
No Representation Rules Them All in Category Discovery. CoRR abs/2311.17055 (2023) - [i138]Niki Amini-Naieni, Tomas Jakab, Andrea Vedaldi, Ronald Clark:
Calibrated Uncertainties for Neural Radiance Fields. CoRR abs/2312.02350 (2023) - [i137]Chuanxia Zheng, Andrea Vedaldi:
Free3D: Consistent Novel View Synthesis without 3D Representation. CoRR abs/2312.04551 (2023) - [i136]Animesh Karnewar, Andrea Vedaldi, Niloy J. Mitra, David Novotný:
GOEnFusion: Gradient Origin Encodings for 3D Forward Diffusion Models. CoRR abs/2312.08744 (2023) - [i135]Minghao Chen, Junyu Xie, Iro Laina, Andrea Vedaldi:
SHAP-EDITOR: Instruction-guided Latent 3D Editing in Seconds. CoRR abs/2312.09246 (2023) - [i134]Stanislaw Szymanowicz, Christian Rupprecht, Andrea Vedaldi:
Splatter Image: Ultra-Fast Single-View 3D Reconstruction. CoRR abs/2312.13150 (2023) - 2022
- [j16]Kai Han
, Sylvestre-Alvise Rebuffi, Sébastien Ehrhardt, Andrea Vedaldi
, Andrew Zisserman
:
AutoNovel: Automatically Discovering and Learning Novel Visual Categories. IEEE Trans. Pattern Anal. Mach. Intell. 44(10): 6767-6781 (2022) - [c163]Vadim Tschernezki, Iro Laina, Diane Larlus, Andrea Vedaldi:
Neural Feature Fusion Fields: 3D Distillation of Self-Supervised 2D Image Representations. 3DV 2022: 443-453 - [c162]Subhabrata Choudhury, Laurynas Karazija, Iro Laina, Andrea Vedaldi, Christian Rupprecht:
Guess What Moves: Unsupervised Video and Image Segmentation by Anticipating Motion. BMVC 2022: 554 - [c161]Xu Ji, Razvan Pascanu, R. Devon Hjelm, Balaji Lakshminarayanan, Andrea Vedaldi:
Test Sample Accuracy Scales with Training Sample Density in Neural Networks. CoLLAs 2022: 629-646 - [c160]Gengshan Yang, Minh Vo, Natalia Neverova, Deva Ramanan
, Andrea Vedaldi, Hanbyul Joo:
BANMo: Building Animatable 3D Neural Models from Many Casual Videos. CVPR 2022: 2853-2863 - [c159]David Novotný, Ignacio Rocco, Samarth Sinha, Alexandre Carlier, Gael Kerchenbaum, Roman Shapovalov, Nikita Smetanin, Natalia Neverova, Benjamin Graham, Andrea Vedaldi:
KeyTr: Keypoint Transporter for 3D Reconstruction of Deformable Objects in Videos. CVPR 2022: 5585-5594 - [c158]Sagar Vaze, Kai Han, Andrea Vedaldi, Andrew Zisserman:
Generalized Category Discovery. CVPR 2022: 7482-7491 - [c157]Luke Melas-Kyriazi, Christian Rupprecht, Iro Laina, Andrea Vedaldi:
Deep Spectral Methods: A Surprisingly Strong Baseline for Unsupervised Semantic Segmentation and Localization. CVPR 2022: 8354-8365 - [c156]Triantafyllos Afouras, Yuki M. Asano, Francois Fagan, Andrea Vedaldi, Florian Metze:
Self-supervised object detection from audio-visual correspondence. CVPR 2022: 10565-10576 - [c155]Andrew Brown
, Cheng-Yang Fu
, Omkar M. Parkhi
, Tamara L. Berg
, Andrea Vedaldi
:
End-to-End Visual Editing with a Generatively Pre-trained Artist. ECCV (15) 2022: 18-35 - [c154]Eldar Insafutdinov, Dylan Campbell
, João F. Henriques, Andrea Vedaldi:
SNeS: Learning Probably Symmetric Neural Surfaces from Incomplete Data. ECCV (32) 2022: 367-383 - [c153]Iro Laina, Yuki M. Asano, Andrea Vedaldi:
Measuring the Interpretability of Unsupervised Representations via Quantized Reversed Probing. ICLR 2022 - [c152]Luke Melas-Kyriazi, Christian Rupprecht, Iro Laina, Andrea Vedaldi:
Finding an Unsupervised Image Segmenter in each of your Deep Generative Models. ICLR 2022 - [c151]Sagar Vaze, Kai Han, Andrea Vedaldi, Andrew Zisserman:
Open-Set Recognition: A Good Closed-Set Classifier is All You Need. ICLR 2022 - [c150]Robert McCraith, Eldar Insafutdinov, Lukás Neumann
, Andrea Vedaldi:
Lifting 2D Object Locations to 3D by Discounting LiDAR Outliers across Objects and Views. ICRA 2022: 2411-2418 - [c149]Laurynas Karazija, Subhabrata Choudhury, Iro Laina, Christian Rupprecht, Andrea Vedaldi:
Unsupervised Multi-Object Segmentation by Predicting Probable Motion Patterns. NeurIPS 2022 - [i133]Sagar Vaze, Kai Han, Andrea Vedaldi, Andrew Zisserman:
Generalized Category Discovery. CoRR abs/2201.02609 (2022) - [i132]Andrew Brown, Cheng-Yang Fu, Omkar M. Parkhi, Tamara L. Berg, Andrea Vedaldi:
End-to-End Visual Editing with a Generatively Pre-Trained Artist. CoRR abs/2205.01668 (2022) - [i131]Luke Melas-Kyriazi, Christian Rupprecht, Iro Laina, Andrea Vedaldi:
Deep Spectral Methods: A Surprisingly Strong Baseline for Unsupervised Semantic Segmentation and Localization. CoRR abs/2205.07839 (2022) - [i130]Subhabrata Choudhury, Laurynas Karazija, Iro Laina, Andrea Vedaldi, Christian Rupprecht:
Guess What Moves: Unsupervised Video and Image Segmentation by Anticipating Motion. CoRR abs/2205.07844 (2022) - [i129]Eldar Insafutdinov, Dylan Campbell, João F. Henriques, Andrea Vedaldi:
SNeS: Learning Probably Symmetric Neural Surfaces from Incomplete Data. CoRR abs/2206.06340 (2022) - [i128]Iro Laina, Yuki M. Asano, Andrea Vedaldi:
Measuring the Interpretability of Unsupervised Representations via Quantized Reverse Probing. CoRR abs/2209.03268 (2022) - [i127]Vadim Tschernezki, Iro Laina, Diane Larlus, Andrea Vedaldi:
Neural Feature Fusion Fields: 3D Distillation of Self-Supervised 2D Image Representations. CoRR abs/2209.03494 (2022) - [i126]Laurynas Karazija, Subhabrata Choudhury, Iro Laina, Christian Rupprecht, Andrea Vedaldi:
Unsupervised Multi-object Segmentation by Predicting Probable Motion Patterns. CoRR abs/2210.12148 (2022) - [i125]Samarth Sinha, Roman Shapovalov, Jeremy Reizenstein, Ignacio Rocco, Natalia Neverova, Andrea Vedaldi, David Novotný:
Common Pets in 3D: Dynamic New-View Synthesis of Real-Life Deformable Categories. CoRR abs/2211.03889 (2022) - [i124]Shangzhe Wu, Ruining Li, Tomas Jakab, Christian Rupprecht, Andrea Vedaldi:
MagicPony: Learning Articulated 3D Animals in the Wild. CoRR abs/2211.12497 (2022) - [i123]Mohamed El Banani, Ignacio Rocco, David Novotný, Andrea Vedaldi, Natalia Neverova, Justin Johnson, Benjamin Graham:
Self-Supervised Correspondence Estimation via Multiview Registration. CoRR abs/2212.03236 (2022) - 2021
- [j15]Han Peng, Weikang Gong, Christian F. Beckmann, Andrea Vedaldi
, Stephen M. Smith
:
Accurate brain age prediction with lightweight deep neural networks. Medical Image Anal. 68: 101871 (2021) - [c148]Hanbyul Joo, Natalia Neverova, Andrea Vedaldi:
Exemplar Fine-Tuning for 3D Human Model Fitting Towards In-the-Wild 3D Human Pose Estimation. 3DV 2021: 42-52 - [c147]Vadim Tschernezki, Diane Larlus, Andrea Vedaldi:
NeuralDiff: Segmenting 3D objects that move in egocentric videos. 3DV 2021: 910-919 - [c146]Subhabrata Choudhury, Iro Laina, Christian Rupprecht, Andrea Vedaldi:
The Curious Layperson: Fine-Grained Image Recognition without Expert Labels. BMVC 2021: 117 - [c145]Triantafyllos Afouras, Honglie Chen, Weidi Xie, Arsha Nagrani, Andrea Vedaldi, Andrew Zisserman:
Audio-Visual Synchronisation in the wild. BMVC 2021: 261 - [c144]Natalia Neverova, Artsiom Sanakoyeu, Patrick Labatut, David Novotný, Andrea Vedaldi:
Discovering Relationships Between Object Categories via Universal Canonical Maps. CVPR 2021: 404-413 - [c143]Philipp Henzler, Jeremy Reizenstein, Patrick Labatut, Roman Shapovalov, Tobias Ritschel, Andrea Vedaldi, David Novotný:
Unsupervised Learning of 3D Object Categories From Videos in the Wild. CVPR 2021: 4700-4709 - [c142]Marvin Eisenberger, David Novotný, Gael Kerchenbaum, Patrick Labatut, Natalia Neverova, Daniel Cremers
, Andrea Vedaldi:
NeuroMorph: Unsupervised Shape Interpolation and Correspondence in One Go. CVPR 2021: 7473-7483 - [c141]Lukás Neumann
, Andrea Vedaldi:
Pedestrian and Ego-Vehicle Trajectory Prediction From Monocular Camera. CVPR 2021: 10204-10212 - [c140]Honglie Chen, Weidi Xie, Triantafyllos Afouras, Arsha Nagrani, Andrea Vedaldi, Andrew Zisserman:
Localizing Visual Sounds the Hard Way. CVPR 2021: 16867-16876 - [c139]Mandela Patrick, Yuki Markus Asano, Polina Kuznetsova, Ruth Fong, João F. Henriques, Geoffrey Zweig, Andrea Vedaldi:
On Compositions of Transformations in Contrastive Self-Supervised Learning. ICCV 2021: 9557-9567 - [c138]Mandela Patrick, Po-Yao Huang, Ishan Misra, Florian Metze, Andrea Vedaldi, Yuki M. Asano, João F. Henriques:
Space-Time Crop & Attend: Improving Cross-modal Video Representation Learning. ICCV 2021: 10540-10552 - [c137]Roman Shapovalov, David Novotný, Benjamin Graham, Patrick Labatut, Andrea Vedaldi:
DensePose 3D: Lifting Canonical Surface Maps of Articulated Objects to the Third Dimension. ICCV 2021: 11709-11719 - [c136]Sylvestre-Alvise Rebuffi, Sébastien Ehrhardt, Kai Han, Andrea Vedaldi, Andrew Zisserman:
LSD-C: Linearly Separable Deep Clusters. ICCVW 2021: 1038-1046 - [c135]Mandela Patrick, Po-Yao Huang, Yuki Markus Asano, Florian Metze, Alexander G. Hauptmann, João F. Henriques, Andrea Vedaldi:
Support-set bottlenecks for video-text representation learning. ICLR 2021 - [c134]Oliver Groth, Chia-Man Hung, Andrea Vedaldi, Ingmar Posner:
Goal-Conditioned End-to-End Visuomotor Control for Versatile Skill Primitives. ICRA 2021: 1319-1325 - [c133]Shangzhe Wu, Christian Rupprecht, Andrea Vedaldi:
Unsupervised Learning of Probably Symmetric Deformable 3D Objects from Images in the Wild (Extended Abstract). IJCAI 2021: 4854-4858 - [c132]Dan Xu, Andrea Vedaldi, João F. Henriques:
Moving SLAM: Fully Unsupervised Deep Learning in Non-Rigid Scenes. IROS 2021: 4611-4617 - [c131]Robert McCraith, Lukás Neumann
, Andrea Vedaldi:
Real Time Monocular Vehicle Velocity Estimation using Synthetic Data. IV 2021: 1406-1412 - [c130]Yuki M. Asano, Christian Rupprecht, Andrew Zisserman, Andrea Vedaldi:
PASS: An ImageNet replacement for self-supervised pretraining without humans. NeurIPS Datasets and Benchmarks 2021 - [c129]Mandela Patrick, Dylan Campbell, Yuki M. Asano, Ishan Misra, Florian Metze, Christoph Feichtenhofer, Andrea Vedaldi, João F. Henriques:
Keeping Your Eye on the Ball: Trajectory Attention in Video Transformers. NeurIPS 2021: 12493-12506 - [c128]Subhabrata Choudhury, Iro Laina, Christian Rupprecht, Andrea Vedaldi:
Unsupervised Part Discovery from Contrastive Reconstruction. NeurIPS 2021: 28104-28118 - [i122]Mandela Patrick, Yuki Markus Asano, Bernie Huang, Ishan Misra, Florian Metze, João F. Henriques, Andrea Vedaldi:
Space-Time Crop & Attend: Improving Cross-modal Video Representation Learning. CoRR abs/2103.10211 (2021) - [i121]Philipp Henzler, Jeremy Reizenstein, Patrick Labatut, Roman Shapovalov, Tobias Ritschel, Andrea Vedaldi, David Novotný:
Unsupervised Learning of 3D Object Categories from Videos in the Wild. CoRR abs/2103.16552 (2021) - [i120]Honglie Chen, Weidi Xie, Triantafyllos Afouras, Arsha Nagrani, Andrea Vedaldi, Andrew Zisserman:
Localizing Visual Sounds the Hard Way. CoRR abs/2104.02691 (2021) - [i119]Triantafyllos Afouras, Yuki Markus Asano, Francois Fagan, Andrea Vedaldi, Florian Metze:
Self-supervised object detection from audio-visual correspondence. CoRR abs/2104.06401 (2021) - [i118]Dan Xu, Andrea Vedaldi, João F. Henriques:
Moving SLAM: Fully Unsupervised Deep Learning in Non-Rigid Scenes. CoRR abs/2105.02195 (2021) - [i117]Luke Melas-Kyriazi, Christian Rupprecht, Iro Laina, Andrea Vedaldi:
Finding an Unsupervised Image Segmenter in Each of Your Deep Generative Models. CoRR abs/2105.08127 (2021) - [i116]Mandela Patrick, Dylan Campbell, Yuki Markus Asano, Ishan Misra, Florian Metze, Christoph Feichtenhofer, Andrea Vedaldi, João F. Henriques:
Keeping Your Eye on the Ball: Trajectory Attention in Video Transformers. CoRR abs/2106.05392 (2021) - [i115]Xu Ji, Razvan Pascanu, R. Devon Hjelm, Andrea Vedaldi, Balaji Lakshminarayanan, Yoshua Bengio:
Predicting Unreliable Predictions by Shattering a Neural Network. CoRR abs/2106.08365 (2021) - [i114]Marvin Eisenberger, David Novotný, Gael Kerchenbaum, Patrick Labatut, Natalia Neverova, Daniel Cremers, Andrea Vedaldi:
NeuroMorph: Unsupervised Shape Interpolation and Correspondence in One Go. CoRR abs/2106.09431 (2021) - [i113]Natalia Neverova, Artsiom Sanakoyeu, Patrick Labatut, David Novotný, Andrea Vedaldi:
Discovering Relationships between Object Categories via Universal Canonical Maps. CoRR abs/2106.09758 (2021) - [i112]Kai Han, Sylvestre-Alvise Rebuffi, Sébastien Ehrhardt, Andrea Vedaldi, Andrew Zisserman:
AutoNovel: Automatically Discovering and Learning Novel Visual Categories. CoRR abs/2106.15252 (2021) - [i111]Shangzhe Wu, Tomas Jakab, Christian Rupprecht, Andrea Vedaldi:
DOVE: Learning Deformable 3D Objects by Watching Videos. CoRR abs/2107.10844 (2021) - [i110]Matan Atzmon, David Novotný, Andrea Vedaldi, Yaron Lipman:
Augmenting Implicit Neural Shape Representations with Explicit Deformation Fields. CoRR abs/2108.08931 (2021) - [i109]Roman Shapovalov, David Novotný, Benjamin Graham, Patrick Labatut, Andrea Vedaldi:
DensePose 3D: Lifting Canonical Surface Maps of Articulated Objects to the Third Dimension. CoRR abs/2109.00033 (2021) - [i108]Robert McCraith, Eldar Insafutdinov, Lukás Neumann, Andrea Vedaldi:
Lifting 2D Object Locations to 3D by Discounting LiDAR Outliers across Objects and Views. CoRR abs/2109.07945 (2021) - [i107]Robert McCraith, Lukás Neumann, Andrea Vedaldi:
Real Time Monocular Vehicle Velocity Estimation using Synthetic Data. CoRR abs/2109.07957 (2021) - [i106]Yuki Markus Asano, Christian Rupprecht, Andrew Zisserman, Andrea Vedaldi:
PASS: An ImageNet replacement for self-supervised pretraining without humans. CoRR abs/2109.13228 (2021) - [i105]Sagar Vaze, Kai Han, Andrea Vedaldi, Andrew Zisserman:
Open-Set Recognition: A Good Closed-Set Classifier is All You Need. CoRR abs/2110.06207 (2021) - [i104]Vadim Tschernezki, Diane Larlus, Andrea Vedaldi:
NeuralDiff: Segmenting 3D objects that move in egocentric videos. CoRR abs/2110.09936 (2021) - [i103]Subhabrata Choudhury, Iro Laina, Christian Rupprecht, Andrea Vedaldi:
The Curious Layperson: Fine-Grained Image Recognition without Expert Labels. CoRR abs/2111.03651 (2021) - [i102]Subhabrata Choudhury, Iro Laina, Christian Rupprecht, Andrea Vedaldi:
Unsupervised Part Discovery from Contrastive Reconstruction. CoRR abs/2111.06349 (2021) - [i101]Honglie Chen, Weidi Xie, Triantafyllos Afouras, Arsha Nagrani, Andrea Vedaldi, Andrew Zisserman:
Audio-Visual Synchronisation in the wild. CoRR abs/2112.04432 (2021) - [i100]Gengshan Yang, Minh Vo, Natalia Neverova, Deva Ramanan, Andrea Vedaldi, Hanbyul Joo:
BANMo: Building Animatable 3D Neural Models from Many Casual Videos. CoRR abs/2112.12761 (2021) - 2020
- [j14]Dmitry Ulyanov
, Andrea Vedaldi, Victor S. Lempitsky:
Deep Image Prior. Int. J. Comput. Vis. 128(7): 1867-1888 (2020) - [j13]David Novotný
, Diane Larlus, Andrea Vedaldi
:
Capturing the Geometry of Object Categories from Video Supervision. IEEE Trans. Pattern Anal. Mach. Intell. 42(2): 261-275 (2020) - [j12]Vassileios Balntas, Karel Lenc
, Andrea Vedaldi
, Tinne Tuytelaars
, Jiri Matas
, Krystian Mikolajczyk:
$\mathbb {H}$H-Patches: A Benchmark and Evaluation of Handcrafted and Learned Local Descriptors. IEEE Trans. Pattern Anal. Mach. Intell. 42(11): 2825-2841 (2020) - [c127]Shangzhe Wu
, Christian Rupprecht, Andrea Vedaldi:
Unsupervised Learning of Probably Symmetric Deformable 3D Objects From Images in the Wild. CVPR 2020: 1-10 - [c126]Sylvestre-Alvise Rebuffi, Sébastien Ehrhardt, Kai Han, Andrea Vedaldi, Andrew Zisserman:
Semi-Supervised Learning with Scarce Annotations. CVPR Workshops 2020: 3294-3302 - [c125]Artsiom Sanakoyeu, Vasil Khalidov, Maureen S. McCarthy, Andrea Vedaldi, Natalia Neverova:
Transferring Dense Pose to Proximal Animal Classes. CVPR 2020: 5232-5241 - [c124]Tomas Jakab, Ankush Gupta, Hakan Bilen
, Andrea Vedaldi:
Self-Supervised Learning of Interpretable Keypoints From Unlabelled Videos. CVPR 2020: 8784-8794 - [c123]Sylvestre-Alvise Rebuffi, Ruth Fong, Xu Ji, Andrea Vedaldi:
There and Back Again: Revisiting Backpropagation Saliency Methods. CVPR 2020: 8836-8845 - [c122]Honglie Chen, Weidi Xie, Andrea Vedaldi, Andrew Zisserman:
Vggsound: A Large-Scale Audio-Visual Dataset. ICASSP 2020: 721-725 - [c121]Yuki Markus Asano, Christian Rupprecht, Andrea Vedaldi:
A critical analysis of self-supervision, or what we can learn from a single image. ICLR 2020 - [c120]Yuki Markus Asano, Christian Rupprecht, Andrea Vedaldi:
Self-labelling via simultaneous clustering and representation learning. ICLR 2020 - [c119]Kai Han, Sylvestre-Alvise Rebuffi, Sébastien Ehrhardt, Andrea Vedaldi, Andrew Zisserman:
Automatically Discovering and Learning New Visual Categories with Ranking Statistics. ICLR 2020 - [c118]Yuki Markus Asano, Mandela Patrick, Christian Rupprecht, Andrea Vedaldi:
Labelling unlabelled videos from scratch with multi-modal self-supervision. NeurIPS 2020 - [c117]Benjamin Biggs, David Novotný, Sébastien Ehrhardt, Hanbyul Joo, Benjamin Graham, Andrea Vedaldi:
3D Multi-bodies: Fitting Sets of Plausible 3D Human Models to Ambiguous Image Data. NeurIPS 2020 - [c116]Sébastien Ehrhardt, Oliver Groth, Áron Monszpart, Martin Engelcke, Ingmar Posner, Niloy J. Mitra, Andrea Vedaldi:
RELATE: Physically Plausible Multi-Object Scene Synthesis Using Structured Latent Spaces. NeurIPS 2020 - [c115]Iro Laina, Ruth Fong, Andrea Vedaldi:
Quantifying Learnability and Describability of Visual Concepts Emerging in Representation Learning. NeurIPS 2020 - [c114]Natalia Neverova, David Novotný, Marc Szafraniec, Vasil Khalidov, Patrick Labatut, Andrea Vedaldi:
Continuous Surface Embeddings. NeurIPS 2020 - [c113]David Novotný, Roman Shapovalov, Andrea Vedaldi:
Canonical 3D Deformer Maps: Unifying parametric and non-parametric methods for dense weakly-supervised category reconstruction. NeurIPS 2020 - [e31]Andrea Vedaldi
, Horst Bischof
, Thomas Brox
, Jan-Michael Frahm:
Computer Vision - ECCV 2020 - 16th European Conference, Glasgow, UK, August 23-28, 2020, Proceedings, Part I. Lecture Notes in Computer Science 12346, Springer 2020, ISBN 978-3-030-58451-1 [contents] - [e30]Andrea Vedaldi
, Horst Bischof
, Thomas Brox
, Jan-Michael Frahm:
Computer Vision - ECCV 2020 - 16th European Conference, Glasgow, UK, August 23-28, 2020, Proceedings, Part II. Lecture Notes in Computer Science 12347, Springer 2020, ISBN 978-3-030-58535-8 [contents] - [e29]Andrea Vedaldi
, Horst Bischof
, Thomas Brox
, Jan-Michael Frahm:
Computer Vision - ECCV 2020 - 16th European Conference, Glasgow, UK, August 23-28, 2020, Proceedings, Part III. Lecture Notes in Computer Science 12348, Springer 2020, ISBN 978-3-030-58579-2 [contents] - [e28]Andrea Vedaldi
, Horst Bischof
, Thomas Brox
, Jan-Michael Frahm:
Computer Vision - ECCV 2020 - 16th European Conference, Glasgow, UK, August 23-28, 2020, Proceedings, Part IV. Lecture Notes in Computer Science 12349, Springer 2020, ISBN 978-3-030-58547-1 [contents] - [e27]Andrea Vedaldi
, Horst Bischof
, Thomas Brox
, Jan-Michael Frahm:
Computer Vision - ECCV 2020 - 16th European Conference, Glasgow, UK, August 23-28, 2020, Proceedings, Part V. Lecture Notes in Computer Science 12350, Springer 2020, ISBN 978-3-030-58557-0 [contents] - [e26]Andrea Vedaldi
, Horst Bischof
, Thomas Brox
, Jan-Michael Frahm:
Computer Vision - ECCV 2020 - 16th European Conference, Glasgow, UK, August 23-28, 2020, Proceedings, Part VI. Lecture Notes in Computer Science 12351, Springer 2020, ISBN 978-3-030-58538-9 [contents] - [e25]Andrea Vedaldi
, Horst Bischof
, Thomas Brox
, Jan-Michael Frahm:
Computer Vision - ECCV 2020 - 16th European Conference, Glasgow, UK, August 23-28, 2020, Proceedings, Part VII. Lecture Notes in Computer Science 12352, Springer 2020, ISBN 978-3-030-58570-9 [contents] - [e24]Andrea Vedaldi
, Horst Bischof
, Thomas Brox
, Jan-Michael Frahm:
Computer Vision - ECCV 2020 - 16th European Conference, Glasgow, UK, August 23-28, 2020, Proceedings, Part VIII. Lecture Notes in Computer Science 12353, Springer 2020, ISBN 978-3-030-58597-6 [contents] - [e23]Andrea Vedaldi
, Horst Bischof
, Thomas Brox
, Jan-Michael Frahm:
Computer Vision - ECCV 2020 - 16th European Conference, Glasgow, UK, August 23-28, 2020, Proceedings, Part IX. Lecture Notes in Computer Science 12354, Springer 2020, ISBN 978-3-030-58544-0 [contents] - [e22]Andrea Vedaldi
, Horst Bischof
, Thomas Brox
, Jan-Michael Frahm:
Computer Vision - ECCV 2020 - 16th European Conference, Glasgow, UK, August 23-28, 2020, Proceedings, Part X. Lecture Notes in Computer Science 12355, Springer 2020, ISBN 978-3-030-58606-5 [contents] - [e21]Andrea Vedaldi
, Horst Bischof
, Thomas Brox
, Jan-Michael Frahm:
Computer Vision - ECCV 2020 - 16th European Conference, Glasgow, UK, August 23-28, 2020, Proceedings, Part XI. Lecture Notes in Computer Science 12356, Springer 2020, ISBN 978-3-030-58620-1 [contents] - [e20]Andrea Vedaldi
, Horst Bischof
, Thomas Brox
, Jan-Michael Frahm:
Computer Vision - ECCV 2020 - 16th European Conference, Glasgow, UK, August 23-28, 2020, Proceedings, Part XII. Lecture Notes in Computer Science 12357, Springer 2020, ISBN 978-3-030-58609-6 [contents] - [e19]Andrea Vedaldi
, Horst Bischof
, Thomas Brox
, Jan-Michael Frahm:
Computer Vision - ECCV 2020 - 16th European Conference, Glasgow, UK, August 23-28, 2020, Proceedings, Part XIII. Lecture Notes in Computer Science 12358, Springer 2020, ISBN 978-3-030-58600-3 [contents] - [e18]Andrea Vedaldi
, Horst Bischof
, Thomas Brox
, Jan-Michael Frahm:
Computer Vision - ECCV 2020 - 16th European Conference, Glasgow, UK, August 23-28, 2020, Proceedings, Part XIV. Lecture Notes in Computer Science 12359, Springer 2020, ISBN 978-3-030-58567-9 [contents] - [e17]Andrea Vedaldi
, Horst Bischof
, Thomas Brox
, Jan-Michael Frahm:
Computer Vision - ECCV 2020 - 16th European Conference, Glasgow, UK, August 23-28, 2020, Proceedings, Part XV. Lecture Notes in Computer Science 12360, Springer 2020, ISBN 978-3-030-58554-9 [contents] - [e16]Andrea Vedaldi
, Horst Bischof
, Thomas Brox
, Jan-Michael Frahm:
Computer Vision - ECCV 2020 - 16th European Conference, Glasgow, UK, August 23-28, 2020, Proceedings, Part XVI. Lecture Notes in Computer Science 12361, Springer 2020, ISBN 978-3-030-58516-7 [contents] - [e15]Andrea Vedaldi
, Horst Bischof
, Thomas Brox
, Jan-Michael Frahm:
Computer Vision - ECCV 2020 - 16th European Conference, Glasgow, UK, August 23-28, 2020, Proceedings, Part XVII. Lecture Notes in Computer Science 12362, Springer 2020, ISBN 978-3-030-58519-8 [contents] - [e14]Andrea Vedaldi
, Horst Bischof
, Thomas Brox
, Jan-Michael Frahm:
Computer Vision - ECCV 2020 - 16th European Conference, Glasgow, UK, August 23-28, 2020, Proceedings, Part XVIII. Lecture Notes in Computer Science 12363, Springer 2020, ISBN 978-3-030-58522-8 [contents] - [e13]Andrea Vedaldi
, Horst Bischof
, Thomas Brox
, Jan-Michael Frahm:
Computer Vision - ECCV 2020 - 16th European Conference, Glasgow, UK, August 23-28, 2020, Proceedings, Part XIX. Lecture Notes in Computer Science 12364, Springer 2020, ISBN 978-3-030-58528-0 [contents] - [e12]Andrea Vedaldi
, Horst Bischof
, Thomas Brox
, Jan-Michael Frahm:
Computer Vision - ECCV 2020 - 16th European Conference, Glasgow, UK, August 23-28, 2020, Proceedings, Part XX. Lecture Notes in Computer Science 12365, Springer 2020, ISBN 978-3-030-58564-8 [contents] - [e11]Andrea Vedaldi
, Horst Bischof
, Thomas Brox
, Jan-Michael Frahm:
Computer Vision - ECCV 2020 - 16th European Conference, Glasgow, UK, August 23-28, 2020, Proceedings, Part XXI. Lecture Notes in Computer Science 12366, Springer 2020, ISBN 978-3-030-58588-4 [contents] - [e10]Andrea Vedaldi
, Horst Bischof
, Thomas Brox
, Jan-Michael Frahm:
Computer Vision - ECCV 2020 - 16th European Conference, Glasgow, UK, August 23-28, 2020, Proceedings, Part XXII. Lecture Notes in Computer Science 12367, Springer 2020, ISBN 978-3-030-58541-9 [contents] - [e9]Andrea Vedaldi
, Horst Bischof
, Thomas Brox
, Jan-Michael Frahm:
Computer Vision - ECCV 2020 - 16th European Conference, Glasgow, UK, August 23-28, 2020, Proceedings, Part XXIII. Lecture Notes in Computer Science 12368, Springer 2020, ISBN 978-3-030-58591-4 [contents] - [e8]Andrea Vedaldi
, Horst Bischof
, Thomas Brox
, Jan-Michael Frahm:
Computer Vision - ECCV 2020 - 16th European Conference, Glasgow, UK, August 23-28, 2020, Proceedings, Part XXIV. Lecture Notes in Computer Science 12369, Springer 2020, ISBN 978-3-030-58585-3 [contents] - [e7]Andrea Vedaldi
, Horst Bischof
, Thomas Brox
, Jan-Michael Frahm:
Computer Vision - ECCV 2020 - 16th European Conference, Glasgow, UK, August 23-28, 2020, Proceedings, Part XXV. Lecture Notes in Computer Science 12370, Springer 2020, ISBN 978-3-030-58594-5 [contents] - [e6]Andrea Vedaldi
, Horst Bischof
, Thomas Brox
, Jan-Michael Frahm:
Computer Vision - ECCV 2020 - 16th European Conference, Glasgow, UK, August 23-28, 2020, Proceedings, Part XXVI. Lecture Notes in Computer Science 12371, Springer 2020, ISBN 978-3-030-58573-0 [contents] - [e5]Andrea Vedaldi
, Horst Bischof
, Thomas Brox
, Jan-Michael Frahm:
Computer Vision - ECCV 2020 - 16th European Conference, Glasgow, UK, August 23-28, 2020, Proceedings, Part XXVII. Lecture Notes in Computer Science 12372, Springer 2020, ISBN 978-3-030-58582-2 [contents] - [e4]Andrea Vedaldi
, Horst Bischof
, Thomas Brox
, Jan-Michael Frahm:
Computer Vision - ECCV 2020 - 16th European Conference, Glasgow, UK, August 23-28, 2020, Proceedings, Part XXVIII. Lecture Notes in Computer Science 12373, Springer 2020, ISBN 978-3-030-58603-4 [contents] - [e3]Andrea Vedaldi
, Horst Bischof
, Thomas Brox
, Jan-Michael Frahm:
Computer Vision - ECCV 2020 - 16th European Conference, Glasgow, UK, August 23-28, 2020, Proceedings, Part XXIX. Lecture Notes in Computer Science 12374, Springer 2020, ISBN 978-3-030-58525-9 [contents] - [e2]Andrea Vedaldi
, Horst Bischof
, Thomas Brox
, Jan-Michael Frahm:
Computer Vision - ECCV 2020 - 16th European Conference, Glasgow, UK, August 23-28, 2020, Proceedings, Part XXX. Lecture Notes in Computer Science 12375, Springer 2020, ISBN 978-3-030-58576-1 [contents] - [i99]Kai Han, Sylvestre-Alvise Rebuffi
, Sébastien Ehrhardt, Andrea Vedaldi, Andrew Zisserman:
Automatically Discovering and Learning New Visual Categories with Ranking Statistics. CoRR abs/2002.05714 (2020) - [i98]Artsiom Sanakoyeu, Vasil Khalidov, Maureen S. McCarthy, Andrea Vedaldi, Natalia Neverova:
Transferring Dense Pose to Proximal Animal Classes. CoRR abs/2003.00080 (2020) - [i97]Mandela Patrick, Yuki Markus Asano, Ruth Fong, João F. Henriques, Geoffrey Zweig, Andrea Vedaldi:
Multi-modal Self-Supervision from Generalized Data Transformations. CoRR abs/2003.04298 (2020) - [i96]Hugo Touvron, Andrea Vedaldi, Matthijs Douze, Hervé Jégou:
Fixing the train-test resolution discrepancy: FixEfficientNet. CoRR abs/2003.08237 (2020) - [i95]Oliver Groth, Chia-Man Hung, Andrea Vedaldi, Ingmar Posner:
Goal-Conditioned End-to-End Visuomotor Control for Versatile Skill Primitives. CoRR abs/2003.08854 (2020) - [i94]Sylvestre-Alvise Rebuffi, Ruth Fong, Xu Ji, Andrea Vedaldi:
There and Back Again: Revisiting Backpropagation Saliency Methods. CoRR abs/2004.02866 (2020) - [i93]Hanbyul Joo, Natalia Neverova, Andrea Vedaldi:
Exemplar Fine-Tuning for 3D Human Pose Fitting Towards In-the-Wild 3D Human Pose Estimation. CoRR abs/2004.03686 (2020) - [i92]Robert McCraith, Lukás Neumann, Andrew Zisserman, Andrea Vedaldi:
Monocular Depth Estimation with Self-supervised Instance Adaptation. CoRR abs/2004.05821 (2020) - [i91]Honglie Chen, Weidi Xie, Andrea Vedaldi, Andrew Zisserman:
VGGSound: A Large-scale Audio-Visual Dataset. CoRR abs/2004.14368 (2020) - [i90]Sylvestre-Alvise Rebuffi, Sébastien Ehrhardt, Kai Han, Andrea Vedaldi, Andrew Zisserman:
LSD-C: Linearly Separable Deep Clusters. CoRR abs/2006.10039 (2020) - [i89]Xu Ji, João F. Henriques, Tinne Tuytelaars, Andrea Vedaldi:
Automatic Recall Machines: Internal Replay, Continual Learning and the Brain. CoRR abs/2006.12323 (2020) - [i88]Yuki Markus Asano, Mandela Patrick, Christian Rupprecht, Andrea Vedaldi:
Labelling unlabelled videos from scratch with multi-modal self-supervision. CoRR abs/2006.13662 (2020) - [i87]Sébastien Ehrhardt, Oliver Groth, Áron Monszpart, Martin Engelcke, Ingmar Posner, Niloy J. Mitra, Andrea Vedaldi:
RELATE: Physically Plausible Multi-Object Scene Synthesis Using Structured Latent Spaces. CoRR abs/2007.01272 (2020) - [i86]David Novotný, Roman Shapovalov, Andrea Vedaldi:
Canonical 3D Deformer Maps: Unifying parametric and non-parametric methods for dense weakly-supervised category reconstruction. CoRR abs/2008.12709 (2020) - [i85]Robert McCraith, Lukás Neumann, Andrea Vedaldi:
Calibrating Self-supervised Monocular Depth Estimation. CoRR abs/2009.07714 (2020) - [i84]Mandela Patrick, Po-Yao Huang, Yuki Markus Asano, Florian Metze, Alexander G. Hauptmann, João F. Henriques, Andrea Vedaldi:
Support-set bottlenecks for video-text representation learning. CoRR abs/2010.02824 (2020) - [i83]Iro Laina, Ruth C. Fong, Andrea Vedaldi:
Quantifying Learnability and Describability of Visual Concepts Emerging in Representation Learning. CoRR abs/2010.14551 (2020) - [i82]Benjamin Biggs, Sébastien Ehrhardt, Hanbyul Joo, Benjamin Graham, Andrea Vedaldi, David Novotný:
3D Multi-bodies: Fitting Sets of Plausible 3D Human Models to Ambiguous Image Data. CoRR abs/2011.00980 (2020) - [i81]Natalia Neverova, David Novotný, Vasil Khalidov, Marc Szafraniec, Patrick Labatut, Andrea Vedaldi:
Continuous Surface Embeddings. CoRR abs/2011.12438 (2020)
2010 – 2019
- 2019
- [j11]Sébastien Ehrhardt, Áron Monszpart
, Niloy J. Mitra, Andrea Vedaldi:
Taking visual motion prediction to new heightfields. Comput. Vis. Image Underst. 181: 14-25 (2019) - [j10]Karel Lenc
, Andrea Vedaldi
:
Understanding Image Representations by Measuring Their Equivariance and Equivalence. Int. J. Comput. Vis. 127(5): 456-476 (2019) - [c112]Fabian B. Fuchs, Oliver Groth, Adam R. Kosiorek, Alex Bewley, Markus Wulfmeier, Andrea Vedaldi, Ingmar Posner:
Scrutinizing and De-Biasing Intuitive Physics with Neural Stethoscopes. BMVC 2019: 73 - [c111]Honglie Chen, Weidi Xie, Andrea Vedaldi, Andrew Zisserman:
AutoCorrect: Deep Inductive Alignment of Noisy Geometric Annotations. BMVC 2019: 152 - [c110]Lukás Neumann
, Andrew Zisserman, Andrea Vedaldi:
Future Event Prediction: If and When. CVPR Workshops 2019: 2935-2943 - [c109]Natalia Neverova, James Thewlis, Riza Alp Güler, Iasonas Kokkinos, Andrea Vedaldi:
Slim DensePose: Thrifty Learning From Sparse Annotations and Motion Cues. CVPR 2019: 10915-10923 - [c108]Ruth Fong, Mandela Patrick, Andrea Vedaldi:
Understanding Deep Networks via Extremal Perturbations and Smooth Masks. ICCV 2019: 2950-2958 - [c107]João F. Henriques, Sébastien Ehrhardt, Samuel Albanie, Andrea Vedaldi:
Small Steps and Giant Leaps: Minimal Newton Solvers for Deep Learning. ICCV 2019: 4762-4771 - [c106]James Thewlis, Samuel Albanie, Hakan Bilen
, Andrea Vedaldi:
Unsupervised Learning of Landmarks by Descriptor Vector Exchange. ICCV 2019: 6360-6370 - [c105]David Novotný, Nikhila Ravi
, Benjamin Graham, Natalia Neverova, Andrea Vedaldi:
C3DPO: Canonical 3D Pose Networks for Non-Rigid Structure From Motion. ICCV 2019: 7687-7696 - [c104]Kai Han, Andrea Vedaldi, Andrew Zisserman:
Learning to Discover Novel Visual Categories via Deep Transfer Clustering. ICCV 2019: 8400-8408 - [c103]Xu Ji, Andrea Vedaldi, João F. Henriques:
Invariant Information Clustering for Unsupervised Image Classification and Segmentation. ICCV 2019: 9864-9873 - [c102]Luca Bertinetto, João F. Henriques, Philip H. S. Torr, Andrea Vedaldi:
Meta-learning with differentiable closed-form solvers. ICLR (Poster) 2019 - [c101]Natalia Neverova, David Novotný, Andrea Vedaldi:
Correlated Uncertainty for Learning Dense Correspondences from Noisy Labels. NeurIPS 2019: 918-926 - [c100]Hugo Touvron, Andrea Vedaldi, Matthijs Douze, Hervé Jégou:
Fixing the train-test resolution discrepancy. NeurIPS 2019: 8250-8260 - [p3]Ruth Fong
, Andrea Vedaldi
:
Explanations for Attributing Deep Neural Network Predictions. Explainable AI 2019: 149-167 - [e1]Wojciech Samek, Grégoire Montavon, Andrea Vedaldi, Lars Kai Hansen
, Klaus-Robert Müller:
Explainable AI: Interpreting, Explaining and Visualizing Deep Learning. Lecture Notes in Computer Science 11700, Springer 2019, ISBN 978-3-030-28953-9 [contents] - [i80]Maxim Berman, Hervé Jégou, Andrea Vedaldi, Iasonas Kokkinos, Matthijs Douze:
MultiGrain: a unified image embedding for classes and instances. CoRR abs/1902.05509 (2019) - [i79]Yuki Markus Asano, Christian Rupprecht, Andrea Vedaldi:
Surprising Effectiveness of Few-Image Unsupervised Feature Learning. CoRR abs/1904.13132 (2019) - [i78]Sylvestre-Alvise Rebuffi
, Sébastien Ehrhardt, Kai Han, Andrea Vedaldi, Andrew Zisserman:
Semi-Supervised Learning with Scarce Annotations. CoRR abs/1905.08845 (2019) - [i77]Sébastien Ehrhardt, Áron Monszpart, Niloy J. Mitra, Andrea Vedaldi:
Unsupervised Intuitive Physics from Past Experiences. CoRR abs/1905.10793 (2019) - [i76]Shangzhe Wu, Christian Rupprecht, Andrea Vedaldi:
Photo-Geometric Autoencoding to Learn 3D Objects from Unlabelled Images. CoRR abs/1906.01568 (2019) - [i75]Natalia Neverova, James Thewlis, Riza Alp Güler, Iasonas Kokkinos, Andrea Vedaldi:
Slim DensePose: Thrifty Learning from Sparse Annotations and Motion Cues. CoRR abs/1906.05706 (2019) - [i74]Hugo Touvron, Andrea Vedaldi, Matthijs Douze, Hervé Jégou:
Fixing the train-test resolution discrepancy. CoRR abs/1906.06423 (2019) - [i73]Tomas Jakab, Ankush Gupta, Hakan Bilen, Andrea Vedaldi:
Learning Landmarks from Unaligned Data using Image Translation. CoRR abs/1907.02055 (2019) - [i72]Honglie Chen, Weidi Xie, Andrea Vedaldi, Andrew Zisserman:
AutoCorrect: Deep Inductive Alignment of Noisy Geometric Annotations. CoRR abs/1908.05263 (2019) - [i71]James Thewlis, Samuel Albanie, Hakan Bilen, Andrea Vedaldi:
Unsupervised Learning of Landmarks by Descriptor Vector Exchange. CoRR abs/1908.06427 (2019) - [i70]Kai Han, Andrea Vedaldi, Andrew Zisserman:
Learning to Discover Novel Visual Categories via Deep Transfer Clustering. CoRR abs/1908.09884 (2019) - [i69]David Novotný, Nikhila Ravi, Benjamin Graham, Natalia Neverova, Andrea Vedaldi:
C3DPO: Canonical 3D Pose Networks for Non-Rigid Structure From Motion. CoRR abs/1909.02533 (2019) - [i68]Ruth Fong, Mandela Patrick, Andrea Vedaldi:
Understanding Deep Networks via Extremal Perturbations and Smooth Masks. CoRR abs/1910.08485 (2019) - [i67]Sylvestre-Alvise Rebuffi, Ruth Fong, Xu Ji, Hakan Bilen, Andrea Vedaldi:
NormGrad: Finding the Pixels that Matter for Training. CoRR abs/1910.08823 (2019) - [i66]Ruth Fong, Andrea Vedaldi:
Occlusions for Effective Data Augmentation in Image Classification. CoRR abs/1910.10651 (2019) - [i65]Yuki Markus Asano, Christian Rupprecht, Andrea Vedaldi:
Self-labelling via simultaneous clustering and representation learning. CoRR abs/1911.05371 (2019) - [i64]Shangzhe Wu, Christian Rupprecht, Andrea Vedaldi:
Unsupervised Learning of Probably Symmetric Deformable 3D Objects from Images in the Wild. CoRR abs/1911.11130 (2019) - 2018
- [j9]Hakan Bilen
, Basura Fernando
, Efstratios Gavves, Andrea Vedaldi
:
Action Recognition with Dynamic Image Networks. IEEE Trans. Pattern Anal. Mach. Intell. 40(12): 2799-2813 (2018) - [c99]Dmitry Ulyanov, Andrea Vedaldi, Victor S. Lempitsky:
It Takes (Only) Two: Adversarial Generator-Encoder Networks. AAAI 2018: 1250-1257 - [c98]Aravindh Mahendran
, James Thewlis
, Andrea Vedaldi:
Cross Pixel Optical-Flow Similarity for Self-supervised Learning. ACCV (5) 2018: 99-116 - [c97]Lukás Neumann
, Andrea Vedaldi:
Tiny People Pose. ACCV (3) 2018: 558-574 - [c96]Lukás Neumann
, Michelle Karg, Shanshan Zhang, Christian Scharfenberger, Eric Piegert, Sarah Mistr, Olga Prokofyeva, Robert Thiel, Andrea Vedaldi, Andrew Zisserman, Bernt Schiele:
NightOwls: A Pedestrians at Night Dataset. ACCV (1) 2018: 691-705 - [c95]Sébastien Ehrhardt
, Áron Monszpart
, Niloy J. Mitra
, Andrea Vedaldi
:
Unsupervised Intuitive Physics from Visual Observations. ACCV (3) 2018: 700-716 - [c94]Ankush Gupta, Andrea Vedaldi, Andrew Zisserman:
Inductive Visual Localisation: Factorised Training for Superior Generalisation. BMVC 2018: 7 - [c93]Karel Lenc, Andrea Vedaldi:
Large scale evaluation of local image feature detectors on homography datasets. BMVC 2018: 122 - [c92]David Novotný, Samuel Albanie, Diane Larlus, Andrea Vedaldi:
Self-Supervised Learning of Geometrically Stable Features Through Probabilistic Introspection. CVPR 2018: 3637-3645 - [c91]Sylvestre-Alvise Rebuffi
, Hakan Bilen
, Andrea Vedaldi:
Efficient Parametrization of Multi-Domain Deep Neural Networks. CVPR 2018: 8119-8127 - [c90]João F. Henriques, Andrea Vedaldi:
MapNet: An Allocentric Spatial Memory for Mapping Environments. CVPR 2018: 8476-8484 - [c89]Ruth Fong, Andrea Vedaldi:
Net2Vec: Quantifying and Explaining How Concepts Are Encoded by Filters in Deep Neural Networks. CVPR 2018: 8730-8738 - [c88]Dmitry Ulyanov, Andrea Vedaldi, Victor S. Lempitsky:
Deep Image Prior. CVPR 2018: 9446-9454 - [c87]Matej Kristan, Ales Leonardis, Jiri Matas
, Michael Felsberg
, Roman P. Pflugfelder, Luka Cehovin Zajc, Tomás Vojír, Goutam Bhat, Alan Lukezic, Abdelrahman Eldesokey, Gustavo Fernández, Álvaro García-Martín, Álvaro Iglesias-Arias, A. Aydin Alatan, Abel González-García, Alfredo Petrosino, Alireza Memarmoghadam
, Andrea Vedaldi, Andrej Muhic, Anfeng He, Arnold W. M. Smeulders, Asanka G. Perera
, Bo Li, Boyu Chen, Changick Kim, Changsheng Xu, Changzhen Xiong, Cheng Tian, Chong Luo, Chong Sun, Cong Hao, Daijin Kim, Deepak Mishra, Deming Chen, Dong Wang, Dongyoon Wee, Efstratios Gavves, Erhan Gundogdu, Erik Velasco-Salido
, Fahad Shahbaz Khan, Fan Yang, Fei Zhao, Feng Li, Francesco Battistone, George De Ath
, Gorthi R. K. Sai Subrahmanyam, Guilherme Sousa Bastos
, Haibin Ling, Hamed Kiani Galoogahi, Hankyeol Lee, Haojie Li, Haojie Zhao, Heng Fan, Honggang Zhang, Horst Possegger, Houqiang Li, Huchuan Lu, Hui Zhi, Huiyun Li, Hyemin Lee, Hyung Jin Chang, Isabela Drummond, Jack Valmadre, Jaime Spencer Martin
, Javaan Singh Chahl
, Jin Young Choi, Jing Li, Jinqiao Wang, Jinqing Qi, Jinyoung Sung, Joakim Johnander, João F. Henriques, Jongwon Choi, Joost van de Weijer
, Jorge Rodríguez Herranz, José M. Martínez, Josef Kittler, Junfei Zhuang, Junyu Gao, Klemen Grm, Lichao Zhang, Lijun Wang, Lingxiao Yang, Litu Rout
, Liu Si, Luca Bertinetto, Lutao Chu, Manqiang Che, Mario Edoardo Maresca, Martin Danelljan, Ming-Hsuan Yang, Mohamed H. Abdelpakey, Mohamed S. Shehata
, Myunggu Kang, Namhoon Lee, Ning Wang, Ondrej Miksik, Payman Moallem
, Pablo Vicente-Moñivar, Pedro Senna, Peixia Li, Philip H. S. Torr, Priya Mariam Raju, Ruihe Qian, Qiang Wang, Qin Zhou, Qing Guo
, Rafael Martin Nieto, Rama Krishna Sai Subrahmanyam Gorthi, Ran Tao, Richard Bowden
, Richard M. Everson, Runling Wang, Sangdoo Yun, Seokeon Choi, Sergio Vivas, Shuai Bai, Shuangping Huang, Sihang Wu, Simon Hadfield
, Siwen Wang, Stuart Golodetz, Ming Tang, Tianyang Xu
, Tianzhu Zhang, Tobias Fischer
, Vincenzo Santopietro, Vitomir Struc, Wei Wang, Wangmeng Zuo, Wei Feng, Wei Wu, Wei Zou, Weiming Hu, Wengang Zhou, Wenjun Zeng, Xiaofan Zhang, Xiaohe Wu, Xiao-Jun Wu, Xinmei Tian, Yan Li, Yan Lu, Yee Wei Law
, Yi Wu, Yiannis Demiris
, Yicai Yang, Yifan Jiao, Yuhong Li, Yunhua Zhang, Yuxuan Sun, Zheng Zhang, Zheng Zhu, Zhen-Hua Feng, Zhihui Wang, Zhiqun He:
The Sixth Visual Object Tracking VOT2018 Challenge Results. ECCV Workshops (1) 2018: 3-53 - [c86]David Novotný
, Samuel Albanie
, Diane Larlus, Andrea Vedaldi
:
Semi-convolutional Operators for Instance Segmentation. ECCV (1) 2018: 89-105 - [c85]Aravindh Mahendran, James Thewlis, Andrea Vedaldi:
Self-supervised Segmentation by Grouping Optical-Flow. ECCV Workshops (5) 2018: 528-534 - [c84]Jack Valmadre
, Luca Bertinetto, João F. Henriques, Ran Tao, Andrea Vedaldi, Arnold W. M. Smeulders, Philip H. S. Torr, Efstratios Gavves:
Long-Term Tracking in the Wild: A Benchmark. ECCV (3) 2018: 692-707 - [c83]Maria Klodt
, Andrea Vedaldi
:
Supervising the New with the Old: Learning SFM from SFM. ECCV (10) 2018: 713-728 - [c82]Oliver Groth, Fabian B. Fuchs, Ingmar Posner, Andrea Vedaldi:
ShapeStacks: Learning Vision-Based Physical Intuition for Generalised Object Stacking. ECCV (1) 2018: 724-739 - [c81]Ankush Gupta, Andrea Vedaldi, Andrew Zisserman:
Learning to Read by Spelling: Towards Unsupervised Text Recognition. ICVGIP 2018: 33:1-33:10 - [c80]Samuel Albanie, Arsha Nagrani, Andrea Vedaldi, Andrew Zisserman:
Emotion Recognition in Speech using Cross-Modal Transfer in the Wild. ACM Multimedia 2018: 292-301 - [c79]Tomas Jakab, Ankush Gupta, Hakan Bilen
, Andrea Vedaldi:
Unsupervised Learning of Object Landmarks through Conditional Image Generation. NeurIPS 2018: 4020-4031 - [c78]James Thewlis, Hakan Bilen
, Andrea Vedaldi:
Modelling and unsupervised learning of symmetric deformable object categories. NeurIPS 2018: 8189-8200 - [c77]Jie Hu, Li Shen, Samuel Albanie, Gang Sun, Andrea Vedaldi:
Gather-Excite: Exploiting Feature Context in Convolutional Neural Networks. NeurIPS 2018: 9423-9433 - [i63]Ruth Fong, Andrea Vedaldi:
Net2Vec: Quantifying and Explaining how Concepts are Encoded by Filters in Deep Neural Networks. CoRR abs/1801.03454 (2018) - [i62]Jack Valmadre, Luca Bertinetto, João F. Henriques, Ran Tao, Andrea Vedaldi, Arnold W. M. Smeulders, Philip H. S. Torr, Efstratios Gavves:
Long-term Tracking in the Wild: A Benchmark. CoRR abs/1803.09502 (2018) - [i61]Sylvestre-Alvise Rebuffi, Hakan Bilen, Andrea Vedaldi:
Efficient parametrization of multi-domain deep neural networks. CoRR abs/1803.10082 (2018) - [i60]David Novotný, Samuel Albanie, Diane Larlus, Andrea Vedaldi:
Self-supervised Learning of Geometrically Stable Features Through Probabilistic Introspection. CoRR abs/1804.01552 (2018) - [i59]Oliver Groth, Fabian Fuchs, Ingmar Posner, Andrea Vedaldi:
ShapeStacks: Learning Vision-Based Physical Intuition for Generalised Object Stacking. CoRR abs/1804.08018 (2018) - [i58]Sébastien Ehrhardt, Áron Monszpart, Niloy J. Mitra, Andrea Vedaldi:
Unsupervised Intuitive Physics from Visual Observations. CoRR abs/1805.05086 (2018) - [i57]João F. Henriques, Sébastien Ehrhardt, Samuel Albanie, Andrea Vedaldi:
Small steps and giant leaps: Minimal Newton solvers for Deep Learning. CoRR abs/1805.08095 (2018) - [i56]Luca Bertinetto, João F. Henriques, Philip H. S. Torr, Andrea Vedaldi:
Meta-learning with differentiable closed-form solvers. CoRR abs/1805.08136 (2018) - [i55]Fabian B. Fuchs, Oliver Groth, Adam R. Kosiorek, Alex Bewley, Markus Wulfmeier, Andrea Vedaldi, Ingmar Posner:
Neural Stethoscopes: Unifying Analytic, Auxiliary and Adversarial Network Probing. CoRR abs/1806.05502 (2018) - [i54]Tomas Jakab, Ankush Gupta, Hakan Bilen, Andrea Vedaldi:
Conditional Image Generation for Learning the Structure of Visual Objects. CoRR abs/1806.07823 (2018) - [i53]Aravindh Mahendran, James Thewlis, Andrea Vedaldi:
Cross Pixel Optical Flow Similarity for Self-Supervised Learning. CoRR abs/1807.05636 (2018) - [i52]Xu Ji, João F. Henriques, Andrea Vedaldi:
Invariant Information Distillation for Unsupervised Image Segmentation and Clustering. CoRR abs/1807.06653 (2018) - [i51]Karel Lenc, Andrea Vedaldi:
Large scale evaluation of local image feature detectors on homography datasets. CoRR abs/1807.07939 (2018) - [i50]Ankush Gupta, Andrea Vedaldi, Andrew Zisserman:
Inductive Visual Localisation: Factorised Training for Superior Generalisation. CoRR abs/1807.08179 (2018) - [i49]David Novotný, Samuel Albanie, Diane Larlus, Andrea Vedaldi:
Semi-convolutional Operators for Instance Segmentation. CoRR abs/1807.10712 (2018) - [i48]Samuel Albanie, Arsha Nagrani, Andrea Vedaldi, Andrew Zisserman:
Emotion Recognition in Speech using Cross-Modal Transfer in the Wild. CoRR abs/1808.05561 (2018) - [i47]Ankush Gupta, Andrea Vedaldi, Andrew Zisserman:
Learning to Read by Spelling: Towards Unsupervised Text Recognition. CoRR abs/1809.08675 (2018) - [i46]Jie Hu, Li Shen, Samuel Albanie, Gang Sun, Andrea Vedaldi:
Gather-Excite: Exploiting Feature Context in Convolutional Neural Networks. CoRR abs/1810.12348 (2018) - 2017
- [j8]Ross B. Girshick, Iasonas Kokkinos, Ivan Laptev, Jitendra Malik, George Papandreou, Andrea Vedaldi, Xiaogang Wang, Shuicheng Yan, Alan L. Yuille
:
Editorial- Deep Learning for Computer Vision. Comput. Vis. Image Underst. 164: 1-2 (2017) - [c76]David Novotný, Diane Larlus, Andrea Vedaldi:
AnchorNet: A Weakly Supervised Network to Learn Geometry-Sensitive Features for Semantic Matching. CVPR 2017: 2867-2876 - [c75]Vassileios Balntas, Karel Lenc, Andrea Vedaldi, Krystian Mikolajczyk:
HPatches: A Benchmark and Evaluation of Handcrafted and Learned Local Descriptors. CVPR 2017: 3852-3861 - [c74]Dmitry Ulyanov, Andrea Vedaldi, Victor S. Lempitsky:
Improved Texture Networks: Maximizing Quality and Diversity in Feed-Forward Stylization and Texture Synthesis. CVPR 2017: 4105-4113 - [c73]Jack Valmadre
, Luca Bertinetto, João F. Henriques, Andrea Vedaldi, Philip H. S. Torr:
End-to-End Representation Learning for Correlation Filter Based Tracking. CVPR 2017: 5000-5008 - [c72]James Thewlis
, Hakan Bilen
, Andrea Vedaldi:
Unsupervised Learning of Object Landmarks by Factorized Spatial Embeddings. ICCV 2017: 3229-3238 - [c71]Ruth C. Fong, Andrea Vedaldi:
Interpretable Explanations of Black Boxes by Meaningful Perturbation. ICCV 2017: 3449-3457 - [c70]David Novotný, Diane Larlus, Andrea Vedaldi:
Learning 3D Object Categories by Looking Around Them. ICCV 2017: 5228-5237 - [c69]Matej Kristan, Ales Leonardis, Jiri Matas
, Michael Felsberg
, Roman P. Pflugfelder, Luka Cehovin Zajc, Tomas Vojir, Gustav Häger, Alan Lukezic, Abdelrahman Eldesokey, Gustavo Fernández, Álvaro García-Martín, Andrej Muhic, Alfredo Petrosino, Alireza Memarmoghadam
, Andrea Vedaldi, Antoine Manzanera
, Antoine Tran, A. Aydin Alatan, Bogdan Mocanu, Boyu Chen, Chang Huang, Changsheng Xu, Chong Sun, Dalong Du, David Zhang, Dawei Du, Deepak Mishra, Erhan Gundogdu, Erik Velasco-Salido
, Fahad Shahbaz Khan
, Francesco Battistone, Gorthi R. K. Sai Subrahmanyam, Goutam Bhat, Guan Huang, Guilherme Sousa Bastos
, Guna Seetharaman, Hongliang Zhang, Houqiang Li, Huchuan Lu, Isabela Drummond, Jack Valmadre, Jae-chan Jeong, Jaeil Cho, Jae-Yeong Lee, Jana Noskova, Jianke Zhu, Jin Gao, Jingyu Liu, Ji-Wan Kim, João F. Henriques, José M. Martínez, Junfei Zhuang, Junliang Xing, Junyu Gao, Kai Chen, Kannappan Palaniappan, Karel Lebeda, Ke Gao, Kris M. Kitani, Lei Zhang, Lijun Wang, Lingxiao Yang, Longyin Wen, Luca Bertinetto, Mahdieh Poostchi, Martin Danelljan, Matthias Mueller
, Mengdan Zhang, Ming-Hsuan Yang, Nianhao Xie, Ning Wang, Ondrej Miksik, Payman Moallem
, Pallavi M. Venugopal, Pedro Senna, Philip H. S. Torr, Qiang Wang, Qifeng Yu, Qingming Huang, Rafael Martin Nieto, Richard Bowden
, Risheng Liu, Ruxandra Tapu, Simon Hadfield
, Siwei Lyu, Stuart Golodetz, Sunglok Choi
, Tianzhu Zhang, Titus B. Zaharia, Vincenzo Santopietro, Wei Zou, Weiming Hu, Wenbing Tao, Wenbo Li
, Wengang Zhou, Xianguo Yu, Xiao Bian, Yang Li, Yifan Xing, Yingruo Fan, Zheng Zhu, Zhipeng Zhang, Zhiqun He:
The Visual Object Tracking VOT2017 Challenge Results. ICCV Workshops 2017: 1949-1972 - [c68]João F. Henriques, Andrea Vedaldi:
Warped Convolutions: Efficient Invariance to Spatial Transformations. ICML 2017: 1461-1469 - [c67]Sylvestre-Alvise Rebuffi, Hakan Bilen
, Andrea Vedaldi:
Learning multiple visual domains with residual adapters. NIPS 2017: 506-516 - [c66]James Thewlis, Hakan Bilen
, Andrea Vedaldi:
Unsupervised learning of object frames by dense equivariant image labelling. NIPS 2017: 844-855 - [p2]David Novotný, Diane Larlus, Andrea Vedaldi:
Generalizing Semantic Part Detectors Across Domains. Domain Adaptation in Computer Vision Applications 2017: 259-273 - [i45]Dmitry Ulyanov, Andrea Vedaldi, Victor S. Lempitsky:
Improved Texture Networks: Maximizing Quality and Diversity in Feed-forward Stylization and Texture Synthesis. CoRR abs/1701.02096 (2017) - [i44]Hakan Bilen, Andrea Vedaldi:
Universal representations: The missing link between faces, text, planktons, and cat breeds. CoRR abs/1701.07275 (2017) - [i43]Sébastien Ehrhardt, Áron Monszpart, Niloy J. Mitra, Andrea Vedaldi:
Learning A Physical Long-term Predictor. CoRR abs/1703.00247 (2017) - [i42]Dmitry Ulyanov, Andrea Vedaldi, Victor S. Lempitsky:
Adversarial Generator-Encoder Networks. CoRR abs/1704.02304 (2017) - [i41]Ruth Fong, Andrea Vedaldi:
Interpretable Explanations of Black Boxes by Meaningful Perturbation. CoRR abs/1704.03296 (2017) - [i40]David Novotný, Diane Larlus, Andrea Vedaldi:
AnchorNet: A Weakly Supervised Network to Learn Geometry-sensitive Features For Semantic Matching. CoRR abs/1704.04749 (2017) - [i39]Vassileios Balntas, Karel Lenc, Andrea Vedaldi, Krystian Mikolajczyk:
HPatches: A benchmark and evaluation of handcrafted and learned local descriptors. CoRR abs/1704.05939 (2017) - [i38]Jack Valmadre, Luca Bertinetto, João F. Henriques, Andrea Vedaldi, Philip H. S. Torr:
End-to-end representation learning for Correlation Filter based tracking. CoRR abs/1704.06036 (2017) - [i37]James Thewlis, Hakan Bilen, Andrea Vedaldi:
Unsupervised learning of object landmarks by factorized spatial embeddings. CoRR abs/1705.02193 (2017) - [i36]David Novotný, Diane Larlus, Andrea Vedaldi:
Learning 3D Object Categories by Looking Around Them. CoRR abs/1705.03951 (2017) - [i35]Sylvestre-Alvise Rebuffi, Hakan Bilen, Andrea Vedaldi:
Learning multiple visual domains with residual adapters. CoRR abs/1705.08045 (2017) - [i34]Sébastien Ehrhardt, Áron Monszpart, Andrea Vedaldi, Niloy J. Mitra:
Learning to Represent Mechanics via Long-term Extrapolation and Interpolation. CoRR abs/1706.02179 (2017) - [i33]James Thewlis, Hakan Bilen, Andrea Vedaldi:
Unsupervised object learning from dense equivariant image labelling. CoRR abs/1706.02932 (2017) - [i32]Jameson Tyler Merkow, Robert B. Lufkin, Kim Nguyen, Stefano Soatto, Zhuowen Tu, Andrea Vedaldi:
DeepRadiologyNet: Radiologist Level Pathology Detection in CT Head Images. CoRR abs/1711.09313 (2017) - [i31]Dmitry Ulyanov, Andrea Vedaldi, Victor S. Lempitsky:
Deep Image Prior. CoRR abs/1711.10925 (2017) - [i30]Sébastien Ehrhardt, Áron Monszpart, Niloy J. Mitra, Andrea Vedaldi:
Taking Visual Motion Prediction To New Heightfields. CoRR abs/1712.09448 (2017) - 2016
- [j7]Max Jaderberg, Karen Simonyan, Andrea Vedaldi, Andrew Zisserman:
Reading Text in the Wild with Convolutional Neural Networks. Int. J. Comput. Vis. 116(1): 1-20 (2016) - [j6]Mircea Cimpoi, Subhransu Maji, Iasonas Kokkinos, Andrea Vedaldi
:
Deep Filter Banks for Texture Recognition, Description, and Segmentation. Int. J. Comput. Vis. 118(1): 65-94 (2016) - [j5]Aravindh Mahendran
, Andrea Vedaldi:
Visualizing Deep Convolutional Neural Networks Using Natural Pre-images. Int. J. Comput. Vis. 120(3): 233-255 (2016) - [c65]Samuel Albanie, Andrea Vedaldi:
Learning Grimaces by Watching TV. BMVC 2016 - [c64]David Novotný, Diane Larlus, Andrea Vedaldi:
I Have Seen Enough: Transferring Parts Across Categories. BMVC 2016 - [c63]James Thewlis, Shuai Zheng, Philip H. S. Torr, Andrea Vedaldi:
Fully-trainable deep matching. BMVC 2016 - [c62]Ankush Gupta, Andrea Vedaldi, Andrew Zisserman:
Synthetic Data for Text Localisation in Natural Images. CVPR 2016: 2315-2324 - [c61]Hakan Bilen
, Andrea Vedaldi:
Weakly Supervised Deep Detection Networks. CVPR 2016: 2846-2854 - [c60]Hakan Bilen
, Basura Fernando, Efstratios Gavves, Andrea Vedaldi, Stephen Gould:
Dynamic Image Networks for Action Recognition. CVPR 2016: 3034-3042 - [c59]Karel Lenc
, Andrea Vedaldi:
Learning Covariant Feature Detectors. ECCV Workshops (3) 2016: 100-117 - [c58]Aravindh Mahendran, Andrea Vedaldi:
Salient Deconvolutional Networks. ECCV (6) 2016: 120-135 - [c57]David Novotný, Diane Larlus, Andrea Vedaldi:
Learning the Structure of Objects from Web Supervision. ECCV Workshops (3) 2016: 218-235 - [c56]Matej Kristan, Ales Leonardis, Jiri Matas
, Michael Felsberg
, Roman P. Pflugfelder, Luka Cehovin
, Tomás Vojír, Gustav Häger, Alan Lukezic, Gustavo Fernández, Abhinav Gupta, Alfredo Petrosino, Alireza Memarmoghadam
, Álvaro García-Martín, Andrés Solís Montero, Andrea Vedaldi, Andreas Robinson, Andy Jinhua Ma, Anton Varfolomieiev
, A. Aydin Alatan, Aykut Erdem
, Bernard Ghanem
, Bin Liu, Bohyung Han, Brais Martínez, Chang-Ming Chang, Changsheng Xu, Chong Sun, Daijin Kim, Dapeng Chen, Dawei Du, Deepak Mishra, Dit-Yan Yeung, Erhan Gundogdu, Erkut Erdem, Fahad Shahbaz Khan, Fatih Porikli, Fei Zhao, Filiz Bunyak
, Francesco Battistone, Gao Zhu, Giorgio Roffo, Gorthi R. K. Sai Subrahmanyam, Guilherme Sousa Bastos
, Guna Seetharaman, Henry Medeiros
, Hongdong Li
, Honggang Qi, Horst Bischof, Horst Possegger, Huchuan Lu, Hyemin Lee, Hyeonseob Nam, Hyung Jin Chang, Isabela Drummond, Jack Valmadre, Jae-chan Jeong, Jaeil Cho, Jae-Yeong Lee, Jianke Zhu, Jiayi Feng, Jin Gao, Jin Young Choi, Jingjing Xiao, Ji-Wan Kim, Jiyeoup Jeong, João F. Henriques, Jochen Lang, Jongwon Choi, José M. Martínez, Junliang Xing, Junyu Gao, Kannappan Palaniappan, Karel Lebeda, Ke Gao, Krystian Mikolajczyk, Lei Qin, Lijun Wang, Longyin Wen, Luca Bertinetto, Madan Kumar Rapuru, Mahdieh Poostchi, Mario Edoardo Maresca, Martin Danelljan, Matthias Mueller
, Mengdan Zhang, Michael Arens, Michel F. Valstar, Ming Tang, Mooyeol Baek, Muhammad Haris Khan
, Naiyan Wang, Nana Fan, Noor Al-Shakarji, Ondrej Miksik, Osman Akin, Payman Moallem
, Pedro Senna, Philip H. S. Torr, Pong C. Yuen, Qingming Huang, Rafael Martin Nieto, Rengarajan Pelapur, Richard Bowden
, Robert Laganière, Rustam Stolkin, Ryan Walsh, Sebastian Bernd Krah, Shengkun Li, Shengping Zhang, Shizeng Yao, Simon Hadfield
, Simone Melzi, Siwei Lyu, Siyi Li, Stefan Becker, Stuart Golodetz, Sumithra Kakanuru, Sunglok Choi
, Tao Hu, Thomas Mauthner, Tianzhu Zhang, Tony P. Pridmore
, Vincenzo Santopietro, Weiming Hu, Wenbo Li
, Wolfgang Hübner, Xiangyuan Lan, Xiaomeng Wang, Xin Li, Yang Li, Yiannis Demiris
, Yifan Wang, Yuankai Qi, Zejian Yuan, Zexiong Cai, Zhan Xu, Zhenyu He, Zhizhen Chi:
The Visual Object Tracking VOT2016 Challenge Results. ECCV Workshops (2) 2016: 777-823 - [c55]Luca Bertinetto, Jack Valmadre
, João F. Henriques, Andrea Vedaldi, Philip H. S. Torr:
Fully-Convolutional Siamese Networks for Object Tracking. ECCV Workshops (2) 2016: 850-865 - [c54]Dmitry Ulyanov, Vadim Lebedev, Andrea Vedaldi, Victor S. Lempitsky:
Texture Networks: Feed-forward Synthesis of Textures and Stylized Images. ICML 2016: 1349-1357 - [c53]Hakan Bilen
, Andrea Vedaldi:
Integrated perception with recurrent multi-task neural networks. NIPS 2016: 235-243 - [c52]Luca Bertinetto, João F. Henriques, Jack Valmadre, Philip H. S. Torr, Andrea Vedaldi:
Learning feed-forward one-shot learners. NIPS 2016: 523-531 - [i29]Dmitry Ulyanov, Vadim Lebedev, Andrea Vedaldi, Victor S. Lempitsky:
Texture Networks: Feed-forward Synthesis of Textures and Stylized Images. CoRR abs/1603.03417 (2016) - [i28]Ankush Gupta, Andrea Vedaldi, Andrew Zisserman:
Synthetic Data for Text Localisation in Natural Images. CoRR abs/1604.06646 (2016) - [i27]Karel Lenc, Andrea Vedaldi:
Learning Covariant Feature Detectors. CoRR abs/1605.01224 (2016) - [i26]Hakan Bilen, Andrea Vedaldi:
Integrated perception with recurrent multi-task neural networks. CoRR abs/1606.01735 (2016) - [i25]Luca Bertinetto, João F. Henriques, Jack Valmadre, Philip H. S. Torr, Andrea Vedaldi:
Learning feed-forward one-shot learners. CoRR abs/1606.05233 (2016) - [i24]Luca Bertinetto, Jack Valmadre, João F. Henriques, Andrea Vedaldi, Philip H. S. Torr:
Fully-Convolutional Siamese Networks for Object Tracking. CoRR abs/1606.09549 (2016) - [i23]David Novotný, Diane Larlus, Andrea Vedaldi:
Learning the semantic structure of objects from Web supervision. CoRR abs/1607.01205 (2016) - [i22]Dmitry Ulyanov, Andrea Vedaldi, Victor S. Lempitsky:
Instance Normalization: The Missing Ingredient for Fast Stylization. CoRR abs/1607.08022 (2016) - [i21]James Thewlis, Shuai Zheng, Philip H. S. Torr, Andrea Vedaldi:
Fully-Trainable Deep Matching. CoRR abs/1609.03532 (2016) - [i20]João F. Henriques, Andrea Vedaldi:
Warped Convolutions: Efficient Invariance to Spatial Transformations. CoRR abs/1609.04382 (2016) - [i19]Samuel Albanie, Andrea Vedaldi:
Learning Grimaces by Watching TV. CoRR abs/1610.02255 (2016) - [i18]Aravindh Mahendran, Hakan Bilen, João F. Henriques, Andrea Vedaldi:
ResearchDoom and CocoDoom: Learning Computer Vision with Games. CoRR abs/1610.02431 (2016) - [i17]Hakan Bilen, Basura Fernando, Efstratios Gavves, Andrea Vedaldi:
Action Recognition with Dynamic Image Networks. CoRR abs/1612.00738 (2016) - 2015
- [j4]Josep M. Gonfaus, Marco Pedersoli, Jordi Gonzàlez
, Andrea Vedaldi, F. Xavier Roca
:
Factorized appearances for object detection. Comput. Vis. Image Underst. 138: 92-101 (2015) - [j3]Marco Pedersoli
, Andrea Vedaldi
, Jordi Gonzàlez
, F. Xavier Roca
:
A coarse-to-fine approach for fast deformable object detection. Pattern Recognit. 48(5): 1844-1853 (2015) - [c51]Karel Lenc
, Andrea Vedaldi:
R-CNN minus R. BMVC 2015: 5.1-5.12 - [c50]Omkar M. Parkhi, Andrea Vedaldi, Andrew Zisserman:
Deep Face Recognition. BMVC 2015: 41.1-41.12 - [c49]Karel Lenc, Andrea Vedaldi:
Understanding image representations by measuring their equivariance and equivalence. CVPR 2015: 991-999 - [c48]Mircea Cimpoi, Subhransu Maji, Andrea Vedaldi:
Deep filter banks for texture recognition and segmentation. CVPR 2015: 3828-3836 - [c47]Aravindh Mahendran, Andrea Vedaldi:
Understanding deep image representations by inverting them. CVPR 2015: 5188-5196 - [c46]Attila Szabó, Andrea Vedaldi, Paolo Favaro:
Building the View Graph of a Category by Exploiting Image Realism. ICCV Workshops 2015: 805-813 - [c45]Andrea Vedaldi, Karel Lenc
:
MatConvNet: Convolutional Neural Networks for MATLAB. ACM Multimedia 2015: 689-692 - [c44]Max Jaderberg, Karen Simonyan, Andrea Vedaldi, Andrew Zisserman:
Deep Structured Output Learning for Unconstrained Text Recognition. ICLR 2015 - [c43]Sobhan Naderi Parizi, Andrea Vedaldi, Andrew Zisserman, Pedro F. Felzenszwalb:
Automatic Discovery and Optimization of Parts for Image Classification. ICLR (Poster) 2015 - [i16]David Novotný, Diane Larlus, Florent Perronnin, Andrea Vedaldi:
Understanding the Fisher Vector: a multimodal part model. CoRR abs/1504.04763 (2015) - [i15]Stavros Tsogkas, Iasonas Kokkinos, George Papandreou, Andrea Vedaldi:
Semantic Part Segmentation with Deep Learning. CoRR abs/1505.02438 (2015) - [i14]Karel Lenc, Andrea Vedaldi:
R-CNN minus R. CoRR abs/1506.06981 (2015) - [i13]Mircea Cimpoi, Subhransu Maji, Iasonas Kokkinos, Andrea Vedaldi:
Deep filter banks for texture recognition, description, and segmentation. CoRR abs/1507.02620 (2015) - [i12]Hakan Bilen, Andrea Vedaldi:
Weakly Supervised Deep Detection Networks. CoRR abs/1511.02853 (2015) - [i11]Aravindh Mahendran, Andrea Vedaldi:
Visualizing Deep Convolutional Neural Networks Using Natural Pre-Images. CoRR abs/1512.02017 (2015) - 2014
- [j2]Karen Simonyan, Andrea Vedaldi
, Andrew Zisserman:
Learning Local Feature Descriptors Using Convex Optimisation. IEEE Trans. Pattern Anal. Mach. Intell. 36(8): 1573-1585 (2014) - [c42]Ken Chatfield, Karen Simonyan, Andrea Vedaldi, Andrew Zisserman:
Return of the Devil in the Details: Delving Deep into Convolutional Nets. BMVC 2014 - [c41]Max Jaderberg, Andrea Vedaldi, Andrew Zisserman:
Speeding up Convolutional Neural Networks with Low Rank Expansions. BMVC 2014 - [c40]Omkar M. Parkhi, Karen Simonyan, Andrea Vedaldi
, Andrew Zisserman:
A Compact and Discriminative Face Track Descriptor. CVPR 2014: 1693-1700 - [c39]Mircea Cimpoi, Subhransu Maji, Iasonas Kokkinos, Sammy Mohamed, Andrea Vedaldi
:
Describing Textures in the Wild. CVPR 2014: 3606-3613 - [c38]Andrea Vedaldi
, Siddharth Mahendran, Stavros Tsogkas, Subhransu Maji, Ross B. Girshick, Juho Kannala, Esa Rahtu
, Iasonas Kokkinos, Matthew B. Blaschko
, David J. Weiss, Ben Taskar, Karen Simonyan, Naomi Saphra, Sammy Mohamed:
Understanding Objects in Detail with Fine-Grained Attributes. CVPR 2014: 3622-3629 - [c37]Max Jaderberg, Andrea Vedaldi
, Andrew Zisserman:
Deep Features for Text Spotting. ECCV (4) 2014: 512-528 - [c36]Karen Simonyan, Andrea Vedaldi, Andrew Zisserman:
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps. ICLR (Workshop Poster) 2014 - [r1]Paolo Favaro, Andrea Vedaldi:
AdaBoost. Computer Vision, A Reference Guide 2014: 16-19 - [i10]Ken Chatfield, Karen Simonyan, Andrea Vedaldi, Andrew Zisserman:
Return of the Devil in the Details: Delving Deep into Convolutional Nets. CoRR abs/1405.3531 (2014) - [i9]Max Jaderberg, Andrea Vedaldi, Andrew Zisserman:
Speeding up Convolutional Neural Networks with Low Rank Expansions. CoRR abs/1405.3866 (2014) - [i8]Max Jaderberg, Karen Simonyan, Andrea Vedaldi, Andrew Zisserman:
Synthetic Data and Artificial Neural Networks for Natural Scene Text Recognition. CoRR abs/1406.2227 (2014) - [i7]Karel Lenc, Andrea Vedaldi:
Understanding image representations by measuring their equivariance and equivalence. CoRR abs/1411.5908 (2014) - [i6]Mircea Cimpoi, Subhransu Maji, Andrea Vedaldi:
Deep convolutional filter banks for texture recognition and segmentation. CoRR abs/1411.6836 (2014) - [i5]Aravindh Mahendran, Andrea Vedaldi:
Understanding Deep Image Representations by Inverting Them. CoRR abs/1412.0035 (2014) - [i4]Max Jaderberg, Karen Simonyan, Andrea Vedaldi, Andrew Zisserman:
Reading Text in the Wild with Convolutional Neural Networks. CoRR abs/1412.1842 (2014) - [i3]Andrea Vedaldi, Karel Lenc:
MatConvNet - Convolutional Neural Networks for MATLAB. CoRR abs/1412.4564 (2014) - 2013
- [c35]Karen Simonyan, Omkar M. Parkhi, Andrea Vedaldi
, Andrew Zisserman:
Fisher Vector Faces in the Wild. BMVC 2013 - [c34]Mayank Juneja, Andrea Vedaldi
, C. V. Jawahar
, Andrew Zisserman:
Blocks That Shout: Distinctive Parts for Scene Classification. CVPR 2013: 923-930 - [c33]Karen Simonyan, Andrea Vedaldi, Andrew Zisserman:
Deep Fisher Networks for Large-Scale Image Classification. NIPS 2013: 163-171 - [i2]Subhransu Maji, Esa Rahtu, Juho Kannala, Matthew B. Blaschko, Andrea Vedaldi:
Fine-Grained Visual Classification of Aircraft. CoRR abs/1306.5151 (2013) - [i1]Mircea Cimpoi, Subhransu Maji, Iasonas Kokkinos, Sammy Mohamed, Andrea Vedaldi:
Describing Textures in the Wild. CoRR abs/1311.3618 (2013) - 2012
- [j1]Andrea Vedaldi
, Andrew Zisserman:
Efficient Additive Kernels via Explicit Feature Maps. IEEE Trans. Pattern Anal. Mach. Intell. 34(3): 480-492 (2012) - [c32]Andrea Vedaldi
, Andrew Zisserman:
Sparse kernel approximations for efficient classification and detection. CVPR 2012: 2320-2327 - [c31]Omkar M. Parkhi, Andrea Vedaldi
, Andrew Zisserman, C. V. Jawahar
:
Cats and dogs. CVPR 2012: 3498-3505 - [c30]Andrea Vedaldi
, Andrew Zisserman:
Self-similar Sketch. ECCV (2) 2012: 87-100 - [c29]Karen Simonyan, Andrea Vedaldi
, Andrew Zisserman:
Descriptor Learning Using Convex Optimisation. ECCV (1) 2012: 243-256 - [c28]Omkar M. Parkhi, Andrea Vedaldi
, Andrew Zisserman:
On-the-fly specific person retrieval. WIAMIS 2012: 1-4 - 2011
- [c27]Ken Chatfield, Victor S. Lempitsky, Andrea Vedaldi, Andrew Zisserman:
The devil is in the details: an evaluation of recent feature encoding methods. BMVC 2011: 1-12 - [c26]Marco Pedersoli
, Andrea Vedaldi
, Jordi Gonzàlez
:
A coarse-to-fine approach for fast deformable object detection. CVPR 2011: 1353-1360 - [c25]Andrea Vedaldi
, Matthew B. Blaschko
, Andrew Zisserman:
Learning equivariant structured output SVM regressors. ICCV 2011: 959-966 - [c24]Omkar M. Parkhi, Andrea Vedaldi
, C. V. Jawahar
, Andrew Zisserman:
The truth about cats and dogs. ICCV 2011: 1427-1434 - [c23]Victor S. Lempitsky, Andrea Vedaldi, Andrew Zisserman:
Pylon Model for Semantic Segmentation. NIPS 2011: 1485-1493 - [c22]Kevin McGuinness, Robin Aly, Shu Chen, Mathieu Frappier, Martijn Kleppe, Hyowon Lee, Roeland Ordelman, Relja Arandjelovic, Mayank Juneja, C. V. Jawahar, Andrea Vedaldi, Jochen Schwenninger, Sebastian Tschöpel, Daniel Schneider, Noel E. O'Connor, Andrew Zisserman, Alan F. Smeaton, Henri Beunders:
AXES at TRECVID 2011. TRECVID 2011 - 2010
- [c21]Sreekanth Vempati, Andrea Vedaldi
, Andrew Zisserman, C. V. Jawahar
:
Generalized RBF feature maps for Efficient Detection. BMVC 2010: 1-11 - [c20]Andrea Vedaldi
, Andrew Zisserman:
Efficient additive kernels via explicit feature maps. CVPR 2010: 3539-3546 - [c19]Andrea Vedaldi
, Brian Fulkerson:
Vlfeat: an open and portable library of computer vision algorithms. ACM Multimedia 2010: 1469-1472 - [c18]Matthew B. Blaschko, Andrea Vedaldi, Andrew Zisserman:
Simultaneous Object Detection and Ranking with Weak Supervision. NIPS 2010: 235-243 - [c17]Mayank Juneja, Siddhartha Chandra, Omkar M. Parkhi, C. V. Jawahar, Andrea Vedaldi, Marcin Marszalek, Andrew Zisserman:
Oxford-IIIT TRECVID 2010 - Notebook paper. TRECVID 2010 - [p1]Andrea Vedaldi
, Haibin Ling, Stefano Soatto:
Knowing a Good Feature When You See It: Ground Truth and Methodology to Evaluate Local Features for Recognition. Computer Vision: Detection, Recognition and Reconstruction 2010: 27-49
2000 – 2009
- 2009
- [c16]Andrea Vedaldi
, Varun Gulshan, Manik Varma, Andrew Zisserman:
Multiple kernels for object detection. ICCV 2009: 606-613 - [c15]Brian Fulkerson, Andrea Vedaldi, Stefano Soatto:
Class segmentation and object localization with superpixel neighborhoods. ICCV 2009: 670-677 - [c14]Andrea Vedaldi, Andrew Zisserman:
Structured output regression for detection with partial truncation. NIPS 2009: 1928-1936 - [c13]Sreekanth Vempati, Mihir Jain, Omkar M. Parkhi, C. V. Jawahar, Marcin Marszalek, Andrea Vedaldi, Andrew Zisserman:
Oxford-IIIT TRECVID 2009 Notebook paper. TRECVID 2009 - 2008
- [c12]Andrea Vedaldi
, Gregorio Guidi, Stefano Soatto:
Joint data alignment up to (lossy) transformations. CVPR 2008 - [c11]Andrea Vedaldi
, Stefano Soatto:
Relaxed matching kernels for robust image comparison. CVPR 2008 - [c10]Brian Fulkerson, Andrea Vedaldi, Stefano Soatto:
Localizing Objects with Smart Dictionaries. ECCV (1) 2008: 179-192 - [c9]Andrea Vedaldi, Stefano Soatto:
Quick Shift and Kernel Methods for Mode Seeking. ECCV (4) 2008: 705-718 - 2007
- [c8]Andrea Vedaldi
, Gregorio Guidi, Stefano Soatto:
Moving Forward in Structure From Motion. CVPR 2007 - [c7]Andrew Rabinovich, Andrea Vedaldi
, Carolina Galleguillos, Eric Wiewiora, Serge J. Belongie
:
Objects in Context. ICCV 2007: 1-8 - [c6]Andrea Vedaldi
, Paolo Favaro, Enrico Grisan
:
Boosting Invariance and Efficiency in Supervised Learning. ICCV 2007: 1-8 - 2006
- [c5]Andrea Vedaldi
, Stefano Soatto:
Local Features, All Grown Up. CVPR (2) 2006: 1753-1760 - [c4]Andrea Vedaldi
, Stefano Soatto:
Viewpoint Induced Deformation Statistics and the Design of Viewpoint Invariant Features: Singularities and Occlusions. ECCV (2) 2006: 360-373 - [c3]Andrea Vedaldi, Stefano Soatto:
A Complexity-Distortion Approach to Joint Pattern Alignment. NIPS 2006: 1425-1432 - 2005
- [c2]Andrea Vedaldi
, Hailin Jin, Paolo Favaro, Stefano Soatto:
KALMANSAC: Robust Filtering by Consensus. ICCV 2005: 633-640 - [c1]Andrea Vedaldi
, Stefano Soatto:
Features for Recognition: Viewpoint Invariance for Non-Planar Scenes. ICCV 2005: 1474-1481
Coauthor Index
aka: Yuki M. Asano
aka: Ruth C. Fong
aka: Rama Krishna Sai Subrahmanyam Gorthi
aka: Gorthi R. K. Sai Subrahmanyam
aka: Philip H. S. Torr
![](https://dblp.uni-trier.de/img/cog.dark.24x24.png)
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