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2020 – today
- 2024
[j10]Juliette Marrie, Michael Arbel, Julien Mairal, Diane Larlus:
On Good Practices for Task-Specific Distillation of Large Pretrained Visual Models. Trans. Mach. Learn. Res. 2024 (2024)- [c43]Mert Bülent Sariyildiz, Philippe Weinzaepfel, Thomas Lucas, Diane Larlus, Yannis Kalantidis:
UNIC: Universal Classification Models via Multi-teacher Distillation. ECCV (4) 2024: 353-371 - [c42]Yannis Kalantidis, Mert Bülent Sariyildiz, Rafael S. Rezende, Philippe Weinzaepfel, Diane Larlus, Gabriela Csurka:
Weatherproofing Retrieval for Localization with Generative AI and Geometric Consistency. ICLR 2024 - [i37]Yannis Kalantidis, Mert Bülent Sariyildiz, Rafael Sampaio de Rezende, Philippe Weinzaepfel, Diane Larlus, Gabriela Csurka:
Weatherproofing Retrieval for Localization with Generative AI and Geometric Consistency. CoRR abs/2402.09237 (2024) - [i36]Juliette Marrie, Michael Arbel, Julien Mairal, Diane Larlus:
On Good Practices for Task-Specific Distillation of Large Pretrained Models. CoRR abs/2402.11305 (2024) - [i35]Tyler L. Hayes, César R. de Souza, Namil Kim, Jiwon Kim, Riccardo Volpi, Diane Larlus:
PANDAS: Prototype-based Novel Class Discovery and Detection. CoRR abs/2402.17420 (2024) - [i34]Gabriela Csurka, Tyler L. Hayes, Diane Larlus, Riccardo Volpi:
What could go wrong? Discovering and describing failure modes in computer vision. CoRR abs/2408.04471 (2024) - [i33]Mert Bülent Sariyildiz, Philippe Weinzaepfel, Thomas Lucas, Diane Larlus, Yannis Kalantidis:
UNIC: Universal Classification Models via Multi-teacher Distillation. CoRR abs/2408.05088 (2024) - 2023
- [c41]Subhankar Roy, Riccardo Volpi, Gabriela Csurka, Diane Larlus:
RaSP: Relation-aware Semantic Prior for Weakly Supervised Incremental Segmentation. CoLLAs 2023: 244-269 - [c40]Mert Bülent Sariyildiz, Karteek Alahari, Diane Larlus, Yannis Kalantidis:
Fake it Till You Make it: Learning Transferable Representations from Synthetic ImageNet Clones. CVPR 2023: 8011-8021 - [c39]Juliette Marrie, Michael Arbel, Diane Larlus, Julien Mairal:
SLACK: Stable Learning of Augmentations with Cold-Start and KL Regularization. CVPR 2023: 24306-24314 - [c38]Mert Bülent Sariyildiz, Yannis Kalantidis, Karteek Alahari, Diane Larlus:
No Reason for No Supervision: Improved Generalization in Supervised Models. ICLR 2023 - [c37]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 - [i32]Subhankar Roy
, Riccardo Volpi, Gabriela Csurka, Diane Larlus:
RaSP: Relation-aware Semantic Prior for Weakly Supervised Incremental Segmentation. CoRR abs/2305.19879 (2023) - [i31]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) - [i30]Juliette Marrie, Michael Arbel, Diane Larlus, Julien Mairal:
SLACK: Stable Learning of Augmentations with Cold-start and KL regularization. CoRR abs/2306.09998 (2023) - 2022
- [j9]Yannis Kalantidis, Carlos Eduardo Rosar Kós Lassance, Jon Almazán, Diane Larlus:
TLDR: Twin Learning for Dimensionality Reduction. Trans. Mach. Learn. Res. 2022 (2022) - [c36]Vadim Tschernezki, Iro Laina, Diane Larlus, Andrea Vedaldi:
Neural Feature Fusion Fields: 3D Distillation of Self-Supervised 2D Image Representations. 3DV 2022: 443-453 - [c35]Riccardo Volpi, Pau de Jorge, Diane Larlus, Gabriela Csurka:
On the Road to Online Adaptation for Semantic Image Segmentation. CVPR 2022: 19162-19173 - [c34]Jon Almazán, ByungSoo Ko, Geonmo Gu, Diane Larlus, Yannis Kalantidis:
Granularity-Aware Adaptation for Image Retrieval Over Multiple Tasks. ECCV (14) 2022: 389-406 - [c33]Ginger Delmas, Rafael Sampaio de Rezende, Gabriela Csurka, Diane Larlus:
ARTEMIS: Attention-based Retrieval with Text-Explicit Matching and Implicit Similarity. ICLR 2022 - [c32]Philippe Weinzaepfel, Thomas Lucas, Diane Larlus, Yannis Kalantidis:
Learning Super-Features for Image Retrieval. ICLR 2022 - [i29]Philippe Weinzaepfel, Thomas Lucas, Diane Larlus, Yannis Kalantidis:
Learning Super-Features for Image Retrieval. CoRR abs/2201.13182 (2022) - [i28]Ginger Delmas, Rafael Sampaio de Rezende, Gabriela Csurka, Diane Larlus:
ARTEMIS: Attention-based Retrieval with Text-Explicit Matching and Implicit Similarity. CoRR abs/2203.08101 (2022) - [i27]Riccardo Volpi, Pau de Jorge, Diane Larlus, Gabriela Csurka:
On the Road to Online Adaptation for Semantic Image Segmentation. CoRR abs/2203.16195 (2022) - [i26]Mert Bülent Sariyildiz, Yannis Kalantidis, Karteek Alahari, Diane Larlus:
Improving the Generalization of Supervised Models. CoRR abs/2206.15369 (2022) - [i25]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) - [i24]Jon Almazán, ByungSoo Ko, Geonmo Gu, Diane Larlus, Yannis Kalantidis:
Granularity-aware Adaptation for Image Retrieval over Multiple Tasks. CoRR abs/2210.02254 (2022) - [i23]Mert Bülent Sariyildiz, Karteek Alahari, Diane Larlus, Yannis Kalantidis:
Fake it till you make it: Learning(s) from a synthetic ImageNet clone. CoRR abs/2212.08420 (2022) - 2021
- [c31]Vadim Tschernezki, Diane Larlus, Andrea Vedaldi:
NeuralDiff: Segmenting 3D objects that move in egocentric videos. 3DV 2021: 910-919 - [c30]Riccardo Volpi, Diane Larlus, Grégory Rogez:
Continual Adaptation of Visual Representations via Domain Randomization and Meta-Learning. CVPR 2021: 4443-4453 - [c29]Sanghyuk Chun, Seong Joon Oh, Rafael Sampaio de Rezende, Yannis Kalantidis, Diane Larlus:
Probabilistic Embeddings for Cross-Modal Retrieval. CVPR 2021: 8415-8424 - [c28]Mert Bülent Sariyildiz, Yannis Kalantidis, Diane Larlus, Karteek Alahari:
Concept Generalization in Visual Representation Learning. ICCV 2021: 9609-9619 - [c27]Vivek Sharma, Naila Murray, Diane Larlus, M. Saquib Sarfraz, Rainer Stiefelhagen, Gabriela Csurka:
Unsupervised Meta-Domain Adaptation for Fashion Retrieval. WACV 2021: 1347-1356 - [c26]Andrés Mafla, Rafael Sampaio de Rezende, Lluís Gómez, Diane Larlus, Dimosthenis Karatzas:
StacMR: Scene-Text Aware Cross-Modal Retrieval. WACV 2021: 2219-2229 - [i22]Sanghyuk Chun, Seong Joon Oh, Rafael Sampaio de Rezende, Yannis Kalantidis, Diane Larlus:
Probabilistic Embeddings for Cross-Modal Retrieval. CoRR abs/2101.05068 (2021) - [i21]Yannis Kalantidis, Carlos Lassance, Jon Almazán, Diane Larlus:
TLDR: Twin Learning for Dimensionality Reduction. CoRR abs/2110.09455 (2021) - [i20]Vadim Tschernezki, Diane Larlus, Andrea Vedaldi:
NeuralDiff: Segmenting 3D objects that move in egocentric videos. CoRR abs/2110.09936 (2021) - [i19]Jonathan Munro, Michael Wray, Diane Larlus, Gabriela Csurka, Dima Damen:
Domain Adaptation in Multi-View Embedding for Cross-Modal Video Retrieval. CoRR abs/2110.12812 (2021) - 2020
- [j8]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) - [c25]Mert Bülent Sariyildiz, Julien Perez, Diane Larlus:
Learning Visual Representations with Caption Annotations. ECCV (8) 2020: 153-170 - [c24]Yannis Kalantidis, Mert Bülent Sariyildiz, Noé Pion, Philippe Weinzaepfel, Diane Larlus:
Hard Negative Mixing for Contrastive Learning. NeurIPS 2020 - [i18]Mert Bülent Sariyildiz, Julien Perez, Diane Larlus:
Learning Visual Representations with Caption Annotations. CoRR abs/2008.01392 (2020) - [i17]Yannis Kalantidis, Mert Bülent Sariyildiz, Noé Pion, Philippe Weinzaepfel, Diane Larlus:
Hard Negative Mixing for Contrastive Learning. CoRR abs/2010.01028 (2020) - [i16]Riccardo Volpi, Diane Larlus, Grégory Rogez:
Continual Adaptation of Visual Representations via Domain Randomization and Meta-learning. CoRR abs/2012.04324 (2020) - [i15]Andrés Mafla, Rafael Sampaio de Rezende, Lluís Gómez, Diane Larlus, Dimosthenis Karatzas:
StacMR: Scene-Text Aware Cross-Modal Retrieval. CoRR abs/2012.04329 (2020) - [i14]Mert Bülent Sariyildiz, Yannis Kalantidis, Diane Larlus, Karteek Alahari:
Concept Generalization in Visual Representation Learning. CoRR abs/2012.05649 (2020)
2010 – 2019
- 2019
- [c23]Michael Wray, Gabriela Csurka, Diane Larlus, Dima Damen:
Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings. ICCV 2019: 450-459 - [i13]Michael Wray, Diane Larlus, Gabriela Csurka, Dima Damen:
Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings. CoRR abs/1908.03477 (2019) - 2018
- [c22]David Novotný, Samuel Albanie, Diane Larlus, Andrea Vedaldi:
Self-Supervised Learning of Geometrically Stable Features Through Probabilistic Introspection. CVPR 2018: 3637-3645 - [c21]David Novotný, Samuel Albanie, Diane Larlus, Andrea Vedaldi:
Semi-convolutional Operators for Instance Segmentation. ECCV (1) 2018: 89-105 - [i12]Jon Almazán, Bojana Gajic, Naila Murray, Diane Larlus:
Re-ID done right: towards good practices for person re-identification. CoRR abs/1801.05339 (2018) - [i11]David Novotný, Samuel Albanie, Diane Larlus, Andrea Vedaldi:
Self-supervised Learning of Geometrically Stable Features Through Probabilistic Introspection. CoRR abs/1804.01552 (2018) - [i10]David Novotný, Samuel Albanie, Diane Larlus, Andrea Vedaldi:
Semi-convolutional Operators for Instance Segmentation. CoRR abs/1807.10712 (2018) - 2017
- [j7]Albert Gordo, Jon Almazán, Jérôme Revaud, Diane Larlus:
End-to-End Learning of Deep Visual Representations for Image Retrieval. Int. J. Comput. Vis. 124(2): 237-254 (2017) - [c20]David Novotný, Diane Larlus, Andrea Vedaldi:
AnchorNet: A Weakly Supervised Network to Learn Geometry-Sensitive Features for Semantic Matching. CVPR 2017: 2867-2876 - [c19]Albert Gordo, Diane Larlus:
Beyond Instance-Level Image Retrieval: Leveraging Captions to Learn a Global Visual Representation for Semantic Retrieval. CVPR 2017: 5272-5281 - [c18]David Novotný, Diane Larlus, Andrea Vedaldi:
Learning 3D Object Categories by Looking Around Them. ICCV 2017: 5228-5237 - [p1]David Novotný, Diane Larlus, Andrea Vedaldi:
Generalizing Semantic Part Detectors Across Domains. Domain Adaptation in Computer Vision Applications 2017: 259-273 - [i9]David Novotný, Diane Larlus, Andrea Vedaldi:
AnchorNet: A Weakly Supervised Network to Learn Geometry-sensitive Features For Semantic Matching. CoRR abs/1704.04749 (2017) - [i8]David Novotný, Diane Larlus, Andrea Vedaldi:
Learning 3D Object Categories by Looking Around Them. CoRR abs/1705.03951 (2017) - 2016
- [j6]José A. Rodríguez-Serrano, Diane Larlus, Zhenwen Dai:
Data-Driven Detection of Prominent Objects. IEEE Trans. Pattern Anal. Mach. Intell. 38(10): 1969-1982 (2016) - [c17]David Novotný, Diane Larlus, Andrea Vedaldi:
I Have Seen Enough: Transferring Parts Across Categories. BMVC 2016 - [c16]David Novotný, Diane Larlus, Andrea Vedaldi:
Learning the Structure of Objects from Web Supervision. ECCV Workshops (3) 2016: 218-235 - [c15]Albert Gordo, Jon Almazán, Jérôme Revaud, Diane Larlus:
Deep Image Retrieval: Learning Global Representations for Image Search. ECCV (6) 2016: 241-257 - [i7]Gabriela Csurka, Diane Larlus, Albert Gordo, Jon Almazán:
What is the right way to represent document images? CoRR abs/1603.01076 (2016) - [i6]Albert Gordo, Jon Almazán, Jérôme Revaud, Diane Larlus:
Deep Image Retrieval: Learning global representations for image search. CoRR abs/1604.01325 (2016) - [i5]David Novotný, Diane Larlus, Andrea Vedaldi:
Learning the semantic structure of objects from Web supervision. CoRR abs/1607.01205 (2016) - [i4]Albert Gordo, Jon Almazán, Jérôme Revaud, Diane Larlus:
End-to-end Learning of Deep Visual Representations for Image Retrieval. CoRR abs/1610.07940 (2016) - 2015
- [c14]Florent Perronnin, Diane Larlus:
Fisher vectors meet Neural Networks: A hybrid classification architecture. CVPR 2015: 3743-3752 - [i3]David Novotný, Diane Larlus, Florent Perronnin, Andrea Vedaldi:
Understanding the Fisher Vector: a multimodal part model. CoRR abs/1504.04763 (2015) - 2014
- [i2]Neda Salamati, Diane Larlus, Gabriela Csurka, Sabine Süsstrunk:
Incorporating Near-Infrared Information into Semantic Image Segmentation. CoRR abs/1406.6147 (2014) - [i1]Yangmuzi Zhang, Diane Larlus, Florent Perronnin:
What makes an Image Iconic? A Fine-Grained Case Study. CoRR abs/1408.4325 (2014) - 2013
- [c13]Gabriela Csurka, Diane Larlus, Florent Perronnin:
What is a good evaluation measure for semantic segmentation?. BMVC 2013 - [c12]José A. Rodríguez-Serrano, Diane Larlus:
Predicting an Object Location Using a Global Image Representation. ICCV 2013: 1729-1736 - 2012
- [c11]Neda Salamati, Diane Larlus, Gabriela Csurka, Sabine Süsstrunk:
Semantic Image Segmentation Using Visible and Near-Infrared Channels. ECCV Workshops (2) 2012: 461-471 - [c10]Rui Hu, Diane Larlus, Gabriela Csurka:
On the use of regions for semantic image segmentation. ICVGIP 2012: 51 - 2011
- [j5]Maja Stikic, Diane Larlus, Sandra Ebert, Bernt Schiele:
Weakly Supervised Recognition of Daily Life Activities with Wearable Sensors. IEEE Trans. Pattern Anal. Mach. Intell. 33(12): 2521-2537 (2011) - [c9]Neda Salamati, Diane Larlus, Gabriela Csurka:
Combining Visible and Near-Infrared Cues for image Categorisation. BMVC 2011: 1-11 - [c8]Luca Marchesotti, Florent Perronnin, Diane Larlus, Gabriela Csurka:
Assessing the aesthetic quality of photographs using generic image descriptors. ICCV 2011: 1784-1791 - 2010
- [j4]Diane Larlus, Jakob Verbeek, Frédéric Jurie:
Category Level Object Segmentation by Combining Bag-of-Words Models with Dirichlet Processes and Random Fields. Int. J. Comput. Vis. 88(2): 238-253 (2010) - [j3]Hakan Cevikalp, Diane Larlus, Marian Neamtu, Bill Triggs, Frédéric Jurie:
Manifold Based Local Classifiers: Linear and Nonlinear Approaches. J. Signal Process. Syst. 61(1): 61-73 (2010) - [c7]Sandra Ebert, Diane Larlus, Bernt Schiele:
Extracting Structures in Image Collections for Object Recognition. ECCV (1) 2010: 720-733
2000 – 2009
- 2009
- [j2]Diane Larlus, Frédéric Jurie:
Latent mixture vocabularies for object categorization and segmentation. Image Vis. Comput. 27(5): 523-534 (2009) - [j1]Joost van de Weijer, Cordelia Schmid, Jakob Verbeek, Diane Larlus:
Learning Color Names for Real-World Applications. IEEE Trans. Image Process. 18(7): 1512-1523 (2009) - [c6]Maja Stikic, Diane Larlus, Bernt Schiele:
Multi-graph Based Semi-supervised Learning for Activity Recognition. ISWC 2009: 85-92 - 2008
- [b1]Diane Larlus:
Création et utilisation de vocabulaires visuels pour la catégorisation d'images et la segmentation de classes d'objets. (Creating and using visual vocabularies for image categorization and object class segmentation). Grenoble Institute of Technology, France, 2008 - [c5]Diane Larlus, Frédéric Jurie:
Combining appearance models and Markov Random Fields for category level object segmentation. CVPR 2008 - 2007
- [c4]Olivier Stasse, Diane Larlus, Baptiste Lagarde, Adrien Escande, François Saïdi, Abderrahmane Kheddar, Kazuhito Yokoi, Frédéric Jurie:
Towards autonomous object reconstruction for visual search by the humanoid robot HRP-2. Humanoids 2007: 151-158 - [c3]Diane Larlus, Frédéric Jurie:
Category level object segmentation - learning to segment objects with latent aspect models. VISAPP (2) 2007: 122-127 - 2006
- [c2]Diane Larlus, Frédéric Jurie:
Latent Mixture Vocabularies for Object Categorization. BMVC 2006: 959-968 - 2005
- [c1]Mark Everingham, Andrew Zisserman, Christopher K. I. Williams, Luc Van Gool, Moray Allan, Christopher M. Bishop, Olivier Chapelle, Navneet Dalal, Thomas Deselaers, Gyuri Dorkó, Stefan Duffner, Jan Eichhorn, Jason D. R. Farquhar, Mario Fritz, Christophe Garcia, Tom Griffiths, Frédéric Jurie, Daniel Keysers, Markus Koskela, Jorma Laaksonen, Diane Larlus, Bastian Leibe, Hongying Meng, Hermann Ney, Bernt Schiele, Cordelia Schmid, Edgar Seemann, John Shawe-Taylor, Amos J. Storkey, Sándor Szedmák, Bill Triggs, Ilkay Ulusoy, Ville Viitaniemi, Jianguo Zhang:
The 2005 PASCAL Visual Object Classes Challenge. MLCW 2005: 117-176
Coauthor Index
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