CVPR18: Session 2-1B: Machine Learning for Computer Vision III HD

Orals (O2-1B) 1. [C10] Efficient Optimization for Rank-Based Loss Functions, Pritish Mohapatra, Michal Rolínek, C.V. Jawahar, Vladimir Kolmogorov, M. Pawan Kumar 2. [C13] Wasserstein Introspective Neural Networks, Kwonjoon Lee, Weijian Xu, Fan Fan, Zhuowen Tu 3. [C16] Taskonomy: Disentangling Task Transfer Learning, Amir R. Zamir, Alexander Sax, William Shen, Leonidas J. Guibas, Jitendra Malik, Silvio Savarese 4. [C19] Maximum Classifier Discrepancy for Unsupervised Domain Adaptation, Kuniaki Saito, Kohei Watanabe, Yoshitaka Ushiku, Tatsuya Harada Spotlights (S2-1B) 1. [C22] Unsupervised Feature Learning via Non-Parametric Instance Discrimination, Zhirong Wu, Yuanjun Xiong, Stella X. Yu, Dahua Lin 2. [D3] Multi-Task Adversarial Network for Disentangled Feature Learning, Yang Liu, Zhaowen Wang, Hailin Jin, Ian Wassell 3. [D6] Learning From Synthetic Data: Addressing Domain Shift for Semantic Segmentation, Swami Sankaranarayanan, Yogesh Balaji, Arpit Jain, Ser Nam Lim, Rama Chellappa 4. [D9] Empirical Study of the Topology and Geometry of Deep Networks, Alhussein Fawzi, Seyed-Mohsen Moosavi-Dezfooli, Pascal Frossard, Stefano Soatto 5. [D12] Boosting Domain Adaptation by Discovering Latent Domains, Massimiliano Mancini, Lorenzo Porzi, Samuel Rota Bulò, Barbara Caputo, Elisa Ricci 6. [D15] Shape From Shading Through Shape Evolution, Dawei Yang, Jia Deng 7. [D18] Weakly Supervised Instance Segmentation Using Class Peak Response, Yanzhao Zhou, Yi Zhu, Qixiang Ye, Qiang Qiu, Jianbin Jiao 8. [D21] Collaborative and Adversarial Network for Unsupervised Domain Adaptation, Weichen Zhang, Wanli Ouyang, Wen Li, Dong Xu 9. [E2] Environment Upgrade Reinforcement Learning for Non-Differentiable Multi-Stage Pipelines, Shuqin Xie, Zitian Chen, Chao Xu, Cewu Lu 10. [E5] Teaching Categories to Human Learners With Visual Explanations, Oisin Mac Aodha, Shihan Su, Yuxin Chen, Pietro Perona, Yisong Yue