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ORCID16th ECCV 2020: Glasgow, UK - Volume 26
- 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 - Jianbo Liu, Junjun He, Jiawei Zhang, Jimmy S. Ren, Hongsheng Li:
EfficientFCN: Holistically-Guided Decoding for Semantic Segmentation. 1-17 - Henry Howard-Jenkins, Yiwen Li, Victor Adrian Prisacariu:
GroSS: Group-Size Series Decomposition for Grouped Architecture Search. 18-33 - Siyuan Liang, Xingxing Wei, Siyuan Yao, Xiaochun Cao:
Efficient Adversarial Attacks for Visual Object Tracking. 34-50 - Xin Peng, Yifu Wang, Ling Gao, Laurent Kneip:
Globally-Optimal Event Camera Motion Estimation. 51-67 - Petrissa Zell, Bodo Rosenhahn, Bastian Wandt:
Weakly-Supervised Learning of Human Dynamics. 68-84 - Royson Lee, Lukasz Dudziak, Mohamed S. Abdelfattah, Stylianos I. Venieris, Hyeji Kim, Hongkai Wen, Nicholas D. Lane:
Journey Towards Tiny Perceptual Super-Resolution. 85-102 - Lucy Chai, David Bau, Ser-Nam Lim, Phillip Isola:
What Makes Fake Images Detectable? Understanding Properties that Generalize. 103-120 - Pau Rodríguez, Issam H. Laradji, Alexandre Drouin, Alexandre Lacoste:
Embedding Propagation: Smoother Manifold for Few-Shot Classification. 121-138 - Xu Chen, Zijian Dong, Jie Song, Andreas Geiger, Otmar Hilliges:
Category Level Object Pose Estimation via Neural Analysis-by-Synthesis. 139-156 - Wonkwang Lee, Donggyun Kim, Seunghoon Hong, Honglak Lee:
High-Fidelity Synthesis with Disentangled Representation. 157-174 - Timothy Duff, Kathlén Kohn, Anton Leykin, Tomás Pajdla:
PL1P - Point-Line Minimal Problems Under Partial Visibility in Three Views. 175-192 - Ke Han, Yan Huang, Zerui Chen, Liang Wang, Tieniu Tan:
Prediction and Recovery for Adaptive Low-Resolution Person Re-Identification. 193-209 - Roei Herzig, Amir Bar, Huijuan Xu, Gal Chechik, Trevor Darrell, Amir Globerson:
Learning Canonical Representations for Scene Graph to Image Generation. 210-227 - Maximilian Augustin, Alexander Meinke, Matthias Hein:
Adversarial Robustness on In- and Out-Distribution Improves Explainability. 228-245 - Sunnie S. Y. Kim, Nicholas I. Kolkin, Jason Salavon, Gregory Shakhnarovich:
Deformable Style Transfer. 246-261 - Senthil Purushwalkam, Tian Ye, Saurabh Gupta, Abhinav Gupta:
Aligning Videos in Space and Time. 262-278 - Yuan Xue, Zihan Zhou, Xiaolei Huang:
Neural Wireframe Renderer: Learning Wireframe to Image Translations. 279-295 - Xiao Zhang, Rui Zhao, Yu Qiao, Hongsheng Li:
RBF-Softmax: Learning Deep Representative Prototypes with Radial Basis Function Softmax. 296-311 - Kelvin Wong, Qiang Zhang, Ming Liang, Bin Yang, Renjie Liao, Abbas Sadat, Raquel Urtasun:
Testing the Safety of Self-driving Vehicles by Simulating Perception and Prediction. 312-329 - Christian Reimers, Jakob Runge, Joachim Denzler:
Determining the Relevance of Features for Deep Neural Networks. 330-346 - Liyi Chen, Weiwei Wu, Chenchen Fu, Xiao Han, Yuntao Zhang:
Weakly Supervised Semantic Segmentation with Boundary Exploration. 347-362 - Wallace P. Lira, Johannes Merz, Daniel Ritchie, Daniel Cohen-Or, Hao (Richard) Zhang:
GANHopper: Multi-hop GAN for Unsupervised Image-to-Image Translation. 363-379 - Philippe Weinzaepfel, Romain Brégier, Hadrien Combaluzier, Vincent Leroy, Grégory Rogez:
DOPE: Distillation of Part Experts for Whole-Body 3D Pose Estimation in the Wild. 380-397 - Nikolas Adaloglou, Nicholas Vretos, Petros Daras:
Multi-view Adaptive Graph Convolutions for Graph Classification. 398-414 - Ke Mei, Chuang Zhu, Jiaqi Zou, Shanghang Zhang:
Instance Adaptive Self-training for Unsupervised Domain Adaptation. 415-430 - Juseung Yun, Byungjoo Kim, Junmo Kim:
Weight Decay Scheduling and Knowledge Distillation for Active Learning. 431-447 - Hai Victor Habi, Roy H. Jennings, Arnon Netzer:
HMQ: Hardware Friendly Mixed Precision Quantization Block for CNNs. 448-463 - Christopher Zach, Huu Le:
Truncated Inference for Latent Variable Optimization Problems: Application to Robust Estimation and Learning. 464-480 - Weizeng Lu, Xi Jia, Weicheng Xie, Linlin Shen, Yicong Zhou, Jinming Duan:
Geometry Constrained Weakly Supervised Object Localization. 481-496 - Kshitij Dwivedi, Jiahui Huang, Radoslaw Martin Cichy, Gemma Roig:
Duality Diagram Similarity: A Generic Framework for Initialization Selection in Task Transfer Learning. 497-513 - Yaniv Benny, Lior Wolf:
OneGAN: Simultaneous Unsupervised Learning of Conditional Image Generation, Foreground Segmentation, and Fine-Grained Clustering. 514-530 - Nikolay Malkin, Anthony Ortiz, Nebojsa Jojic:
Mining Self-similarity: Label Super-Resolution with Epitomic Representations. 531-547 - Dongsheng An, Yang Guo, Min Zhang, Xin Qi, Na Lei, Xianfeng Gu:
AE-OT-GAN: Training GANs from Data Specific Latent Distribution. 548-564 - Thomas Kehrenberg, Myles Bartlett, Oliver Thomas, Novi Quadrianto:
Null-Sampling for Interpretable and Fair Representations. 565-580 - Lam Huynh, Phong Nguyen-Ha, Jiri Matas, Esa Rahtu, Janne Heikkilä:
Guiding Monocular Depth Estimation Using Depth-Attention Volume. 581-597 - Adam W. Harley, Shrinidhi Kowshika Lakshmikanth, Paul Schydlo, Katerina Fragkiadaki:
Tracking Emerges by Looking Around Static Scenes, with Neural 3D Mapping. 598-614 - Yuanyi Zhong, Jianfeng Wang, Jian Peng, Lei Zhang:
Boosting Weakly Supervised Object Detection with Progressive Knowledge Transfer. 615-631 - Ayan Das, Yongxin Yang, Timothy M. Hospedales, Tao Xiang, Yi-Zhe Song:
BézierSketch: A Generative Model for Scalable Vector Sketches. 632-647 - Zeqi Li, Ruowei Jiang, Parham Aarabi:
Semantic Relation Preserving Knowledge Distillation for Image-to-Image Translation. 648-663 - Brady Zhou, Nimit Kalra, Philipp Krähenbühl:
Domain Adaptation Through Task Distillation. 664-680 - Chenglin Yang, Adam Kortylewski, Cihang Xie, Yinzhi Cao, Alan L. Yuille:
PatchAttack: A Black-Box Texture-Based Attack with Reinforcement Learning. 681-698 - Yu Liu, Sarah Parisot, Gregory G. Slabaugh, Xu Jia, Ales Leonardis, Tinne Tuytelaars:
More Classifiers, Less Forgetting: A Generic Multi-classifier Paradigm for Incremental Learning. 699-716 - Bram Wallace, Bharath Hariharan:
Extending and Analyzing Self-supervised Learning Across Domains. 717-734 - Sayan Rakshit, Dipesh Tamboli, Pragati Shuddhodhan Meshram, Biplab Banerjee, Gemma Roig, Subhasis Chaudhuri:
Multi-source Open-Set Deep Adversarial Domain Adaptation. 735-750 - Wen-Hsuan Chu, Kris M. Kitani:
Neural Batch Sampling with Reinforcement Learning for Semi-supervised Anomaly Detection. 751-766 - Baoxiong Jia, Yixin Chen, Siyuan Huang, Yixin Zhu, Song-Chun Zhu:
LEMMA: A Multi-view Dataset for LEarning Multi-agent Multi-task Activities. 767-786
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