A compilation of domain-shift related papers in reinforcement learning

• Domain Adaption
  • Partial Transfer or OpenSet adaptation
• Domain Shift in Reinforcement Learning
  • Inverse Dynamic Model
  • Domain Randomization
• Segmentation
  • Semantic Segmentation
  • Domain Transfer for Semantic Segmentation
  • Domain Transfer for Depth Estimation
  • From higher level information (classification) to lower level information (segmentation)
• Hierarchical Reinforcement Learning
• Meta-Learning
• Metric-Learning
• Transfer-Learning
• Few-Shot Learning
  • Zero-Shot Learning
• Feature Learning
• Evaluating Performance of Policies
• Self-Training
• Research Blogs
• Datasets
• Clustering
• Others
• Key Papers
• TO-DOs

• Awesome Transfer Learning [github]
• (HP) A DIRT-T Approach to Unsupervised Domain Adaptation [pdf][slides]
  • Rui Shu, Hung Bui, Hirokazu Narui, Stefano Ermon. ICLR'18
• Learning Transferrable Representations for Unsupervised Domain Adaptation [pdf]
  • Ozan Sener, Hyun Oh Song, Ashutosh Saxena, Silvio Savarese. NIPS'16
• (WC) Domain Separation Networks [pdf]
  • Konstantinos Bousmalis, George Trigeorgis, Nathan Silberman, Dilip Krishnan, Dumitru Erhan. NIPS'16
• Unsupervised Domain Adaptation with Residual Transfer Networks [pdf]
  • Mingsheng Long, Han Zhu, Jianmin Wang, Michael I. Jordan. NIPS'16
• (HP) Multi-Adversarial Domain Adaptation. [pdf][slides]
  • Zhongyi Pei, Zhangjie Cao, Mingsheng Long, and Jianmin Wang. AAAI'18
• (HP) Multimodal Unsupervised Image-to-Image Translation [pdf][slides]
  • Xun Huang, Ming-Yu Liu, Serge Belongie, Jan Kautz. arXiv'18
• Learning to cluster in order to transfer across domains and tasks [pdf] ---> already presented by Prof.Chiu
  • Yen-Chang Hsu, Zhaoyang Lv, Zsolt Kira. ICLR'18
• (HP) Unupervised Domain Adaptation by Backpropagation [pdf]
  • Yaroslav Ganin, Victor Lempitsky. arXiv'14 - Eric Tzeng, Judy Hoffman, Kate Saenko, Trevor Darrell. CVPR'17
• (WC) Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks [pdf]
  • Konstantinos Bousmalis, Nathan Silberman, David Dohan, Dumitru Erhan, Dilip Krishnan. CVPR'17
• (BS) Revisiting Batch Normalization For Practical Domain Adaptation [pdf] [ppt]
  • Yanghao Li, Naiyan Wang, Jianping Shi, Jiaying Liu, Xiaodi Hou. ICLR'17 WorkShop
• (WC) CyCADA: Cycle-Consistent Adversarial Domain Adaptation [pdf]
  • Judy Hoffman, Eric Tzeng, Taesung Park, Jun-Yan Zhu, Phillip Isola, Kate Saenko, Alexei A. Efros, Trevor Darrell. arXiv'17
• (HP) Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization [pdf]
  • Xun Huang, Serge Belongie. ICCV'17
• Curriculum Domain Adaptation for Semantic Segmentation of Urban Scenes [pdf]
  • Yang Zhang, Philip David, Boqing Gong. ICCV'17
• (HP) Associative Domain Adaptation [pdf][slides]
  • Philip Haeusser, Thomas Frerix, Alexander Mordvintsev, Daniel Cremers. ICCV'17
• (WC) Cross-Domain Self-supervised Multi-task Feature Learning using Synthetic Imagery [pdf]
  • Zhongzheng Ren and Yong Jae Lee. CVPR'18
• (BS) Simulated+Unsupervised Learning With Adaptive Data Generation and Bidirectional Mappings [pdf]
  • Kangwook Lee, Hoon Kim, Changho Suh. ICLR'18
• (WC) Deep CORAL: Correlation Alignment for Deep Domain Adaptation [pdf]
  • Baochen Sun, Kate Saenko. ECCV'16
• Self-ensembling for visual domain adaptation [pdf]
  • Geoff French, Michal Mackiewicz, Mark Fisher. ICLR'18
• (WC) Minimal-Entropy Correlation Alignment for Unsupervised Deep Domain Adaptation [pdf]
  • Pietro Morerio, Jacopo Cavazza, Vittorio Murino. ICLR'18
• Multiple Source Domain Adaptation with Adversarial Learning [pdf]
  • Han Zhao, Shanghang Zhang, Guanhang Wu, Jo~{a}o P. Costeira, Jos'{e} M. F. Moura, Geoffrey J. Gordon. ICLR'18
• Generalizing Across Domains via Cross-Gradient Training [pdf]
  • Shiv Shankar*, Vihari Piratla*, Soumen Chakrabarti, Siddhartha Chaudhuri, Preethi Jyothi, Sunita Sarawagi. ICLR'18
• Identifying Analogies Across Domains [pdf]
  • Yedid Hoshen, Lior Wolf. ICLR'18
• AdaDepth: Unsupervised Content Congruent Adaptation for Depth Estimation [pdf]
  • Jogendra Nath Kundu, Phani Krishna Uppala, Anuj Pahuja, R. Venkatesh Babu. CVPR'18
• (WC) Maximum Classifier Discrepancy for Unsupervised Domain Adaptation [pdf]
  • Kuniaki Saito, Kohei Watanabe, Yoshitaka Ushiku, Tatsuya Harada. CVPR'18
• Boosting Domain Adaptation by Discovering Latent Domains [pdf]
  • Massimiliano Mancini, Lorenzo Porzi, Samuel Rota Bulò, Barbara Caputo, Elisa Ricci. CVPR'18
• Collaborative and Adversarial Network for Unsupervised Domain Adaptation (pdf-404)
  • Weichen Zhang, Wanli Ouyang, Wen Li, Dong Xu. CVPR'18
• (WC) Generate To Adapt: Aligning Domains using Generative Adversarial Networks [pdf]
  • Swami Sankaranarayanan, Yogesh Balaji, Carlos D. Castillo, Rama Chellappa. CVPR'18
• (WC) Detach and Adapt: Learning Cross-Domain Disentangled Deep Representation [pdf]
  • Yen-Cheng Liu, Yu-Ying Yeh, Tzu-Chien Fu, Sheng-De Wang, Wei-Chen Chiu, Yu-Chiang Frank Wang. CVPR'18
• (WC) Learning from Synthetic Data: Addressing Domain Shift for Semantic Segmentation [pdf]
  • Swami Sankaranarayanan, Yogesh Balaji, Arpit Jain, Ser Nam Lim, Rama Chellappa. CVPR'18
• Image-Image Domain Adaptation With Preserved Self-Similarity and Domain-Dissimilarity for Person Re-Identification [pdf]
  • Weijian Deng, Liang Zheng, Guoliang Kang, Yi Yang, Qixiang Ye, Jianbin Jiao. CVPR'18
• (WC) Duplex Generative Adversarial Network for Unsupervised Domain Adaptation [pdf]
  • Lanqing Hu, Meina Kan, Shiguang Shan, Xilin Chen. CVPR'18
• Real-Time Monocular Depth Estimation Using Synthetic Data With Domain Adaptation via Image Style Transfer [pdf]
  • Amir Atapour-Abarghouei, Toby P. Breckon. CVPR'18
• Domain Adaptive Faster R-CNN for Object Detection in the Wild [pdf]
  • Yuhua Chen, Wen Li, Christos Sakaridis, Dengxin Dai, Luc Van Gool. CVPR'18
• Aligning Infinite-Dimensional Covariance Matrices in Reproducing Kernel Hilbert Spaces for Domain Adaptation (pdf-404)
  • Zhen Zhang, Mianzhi Wang, Yan Huang, Arye Nehorai. CVPR'18
• Deep Cocktail Network: Multi-Source Unsupervised Domain Adaptation With Category Shift [pdf]
  • Ruijia Xu, Ziliang Chen, Wangmeng Zuo, Junjie Yan, Liang Lin. CVPR'18
• Residual Parameter Transfer for Deep Domain Adaptation [pdf]
  • Artem Rozantsev, Mathieu Salzmann, Pascal Fua. CVPR'18
• (Stefanie) Image to Image Translation for Domain Adaptation [pdf]
  • Zak Murez, Soheil Kolouri, David Kriegman, Ravi Ramamoorthi, Kyungnam Kim. CVPR'18
• Cross-Domain Weakly-Supervised Object Detection Through Progressive Domain Adaptation [pdf]
  • Naoto Inoue, Ryosuke Furuta, Toshihiko Yamasaki, Kiyoharu Aizawa. CVPR'18
• Camera Style Adaptation for Person Re-Identification [pdf]
  • Zhun Zhong, Liang Zheng, Zhedong Zheng, Shaozi Li, Yi Yang. CVPR'18
• Adversarial Feature Augmentation for Unsupervised Domain Adaptation [pdf]
  • Riccardo Volpi, Pietro Morerio, Silvio Savarese, Vittorio Murino. CVPR'18
• Fully Convolutional Adaptation Networks for Semantic Segmentation [pdf]
  • Yiheng Zhang, Zhaofan Qiu, Ting Yao, Dong Liu, Tao Mei. CVPR'18
• ROAD: Reality Oriented Adaptation for Semantic Segmentation of Urban Scenes [pdf]
  • Yuhua Chen, Wen Li, Luc Van Gool. CVPR'18
• Re-Weighted Adversarial Adaptation Network for Unsupervised Domain Adaptation (pdf-404)
  • Qingchao Chen, Yang Liu, Zhaowen Wang, Ian Wassell, Kevin Chetty. CVPR'18
• Unsupervised Domain Adaptation with Similarity Learning [pdf]
  • Pedro O. Pinheiro. CVPR'18
• People, Penguins and Petri Dishes: Adapting Object Counting Models To New Visual Domains And Object Types Without Forgetting [pdf]
  • Mark Marsden, Kevin McGuinness, Suzanne Little, Ciara E. Keogh, Noel E. O'Connor. CVPR'18
• From Source to Target and Back: Symmetric Bi-Directional Adaptive GAN [pdf]
  • Paolo Russo, Fabio Maria Carlucci, Tatiana Tommasi, Barbara Caputo. CVPR'18
• Importance Weighted Adversarial Nets for Partial Domain Adaptation [pdf]
  • Jing Zhang, Zewei Ding, Wanqing Li, Philip Ogunbona. CVPR'18
• (WC) Cross-Domain Self-Supervised Multi-Task Feature Learning Using Synthetic Imagery [pdf]
  • Zhongzheng Ren, Yong Jae Lee. CVPR'18
• Zoom and Learn: Generalizing Deep Stereo Matching to Novel Domains [pdf]
  • Jiahao Pang, Wenxiu Sun, Chengxi Yang, Jimmy Ren, Ruichao Xiao, Jin Zeng, Liang Lin. CVPR'18
• Efficient parametrization of multi-domain deep neural networks [pdf]
  • Sylvestre-Alvise Rebuffi, Hakan Bilen, Andrea Vedaldi. CVPR'18
• Domain Generalization With Adversarial Feature Learning (pdf-404)
  • Haoliang Li, Sinno Jialin Pan, Shiqi Wang, Alex C. Kot. CVPR'18
• (YC) Adversarial Discriminative Domain Adaptation [pdf]
  • Eric Tzeng, Judy Hoffman, Kate Saenko, Trevor Darrell. CVPR'17
• AugGAN: Cross Domain Adaptation with GAN-based Data Augmentation [pdf]
  • Sheng-Wei Huang, Che-Tsung Lin, Shu-Ping Chen, Yen-Yi Wu, Po-Hao Hsu, Shang-Hong Lai. ECCV'18
• DeepJDOT: Deep Joint Distribution Optimal Transport for Unsupervised Domain Adaptation [pdf]
  • Bharath Bhushan Damodaran, Benjamin Kellenberger, Remi Flamary, Devis Tuia, Nicolas Courty. ECCV'18
• (HJ) Domain Adaptation through Synthesis forUnsupervised Person Re-identification [pdf]
  • Slawomir Bak, Peter Carr, Jean-Francois Lalonde. ECCV'18
• (AH) Open Set Domain Adaptation by Backpropagation [pdf]
  • Kuniaki Saito, Shohei Yamamoto, Yoshitaka Ushiku, Tatsuya Harada. ECCV'18
• (HJ) Deep Adversarial Attention Alignment forUnsupervised Domain Adaptation:the Benefit of Target Expectation Maximization [pdf]
  • Guoliang Kang, Liang Zheng, Yan Yan, Zikun Liu, Yi Yang. ECCV'18
• Adversarial Multiple Source Domain Adaptation [pdf]
  • Han Zhao · Shanghang Zhang · Guanhang Wu · José M. F. Moura · Joao P Costeira · Geoffrey Gordon. NIPS'19

• Open Set Domain Adaptation [pdf]
  • Pau Panareda Busto, Juergen Gall. ICCV'17
• (HP) Label Efficient Learning of Transferable Representations acrosss Domains and Tasks [pdf]
  • Zelun Luo, Yuliang Zou, Judy Hoffman, Li Fei-Fei. NIPS'17
• (YC) Partial Adversarial Domain Adaptation [pdf]
  • Zhangjie Cao, Lijia Ma, Mingsheng Long, Jianmin Wang. ECCV'18
• (AH) Open Set Domain Adaptation by Backpropagation [pdf]
  • Kuniaki Saito, Shohei Yamamoto, Yoshitaka Ushiku, Tatsuya Harada. ECCV'18
• (HP) Unsupervised Domain Adaptation for Distance Metric Learning [pdf]
  • Anonymous. ICLR'19 under review as a conference paper
• (WC) Importance Weighted Adversarial Nets for Partial Domain Adaptation [pdf]
  • Jing Zhang, Zewei Ding, Wanqing Li, Philip Ogunbona. CVPR'18
• (WC, BS) Partial Transfer Learning With Selective Adversarial Networks. [pdf]
  • Zhangjie Cao, Mingsheng Long, Jianmin Wang, Michael I. Jordan. CVPR'18
• (HP) Boosting Domain Adaptation by Discovering Latent Domains [pdf]
  • Massimiliano Mancini, Lorenzo Porzi, Samuel Rota Bulò, Barbara Caputo, Elisa Ricci. CVPR'18

• Blazingly Fast Video Object Segmentation with Pixel-Wise Metric Learning [pdf]
  • Yuhua Chen, Jordi Pont-Tuset, Alberto Montes, Luc Van Gool. CVPR'18
• Learning a Discriminative Feature Network for Semantic Segmentation [pdf]
  • Changqian Yu, Jingbo Wang, Chao Peng, Changxin Gao, Gang Yu, Nong Sang. CVPR'18
• Revisiting Dilated Convolution: A Simple Approach for Weakly- and Semi-Supervised Semantic Segmentation [pdf]
  • Yunchao Wei, Huaxin Xiao, Honghui Shi, Zequn Jie, Jiashi Feng, Thomas S. Huang. CVPR'18

• DenseASPP for Semantic Segmentation in Street Scenes [pdf]
  • Maoke Yang, Kun Yu, Chi Zhang, Zhiwei Li, Kuiyuan Yang. CVPR'18
• Dense Decoder Shortcut Connections for Single-Pass Semantic Segmentation [pdf]
  • Piotr Bilinski, Victor Prisacariu. CVPR'18
• Context Encoding for Semantic Segmentation [pdf]
  • Hang Zhang, Kristin Dana, Jianping Shi, Zhongyue Zhang, Xiaogang Wang, Ambrish Tyagi, Amit Agrawal. CVPR'18
• 3D Semantic Segmentation With Submanifold Sparse Convolutional Networks [pdf]
  • Benjamin Graham, Martin Engelcke, Laurens van der Maaten. CVPR'18
• ExFuse: Enhancing Feature Fusion for Semantic Segmentation [pdf]
  • Zhenli Zhang, Xiangyu Zhang, Chao Peng, Xiangyang Xue, Jian Sun. ECCV'18

• (HP) Learning from Synthetic Data: Addressing Domain Shift for Semantic Segmentation [pdf]
  • Swami Sankaranarayanan, Yogesh Balaji, Arpit Jain, Ser Nam Lim, Rama Chellappa. CVPR'18
• (HP) Fully Convolutional Adaptation Networks for Semantic Segmentation [pdf]
  • Yiheng Zhang, Zhaofan Qiu, Ting Yao, Dong Liu, Tao Mei. CVPR'18
• (HP) Conditional Generative Adversarial Network for Structured Domain Adaptation [pdf]
  • Weixiang Hong, Zhenzhen Wang, Ming Yang, Junsong Yuan. CVPR'18
• (WC, HP) Learning to Adapt Structured Output Space for Semantic Segmentation [pdf]
  • Yi-Hsuan Tsai, Wei-Chih Hung, Samuel Schulter, Kihyuk Sohn, Ming-Hsuan Yang, Manmohan Chandraker. CVPR'18
• (HP) ROAD: Reality Oriented Adaptation for Semantic Segmentation of Urban Scenes [pdf]
  • Yuhua Chen, Wen Li, Luc Van Gool. CVPR'18
• (WC, HP) DCAN: Dual Channel-wise Alignment Networks for Unsupervised Scene Adaptation [pdf]
  • Zuxuan Wu, Xintong Han, Yen-Liang Lin, Mustafa Gokhan Uzunbas, Tom Goldstein, Ser Nam Lim, Larry S. Davis. ECCV'18
• (WC, HP) Effective Use of Synthetic Data forUrban Scene Semantic Segmentation [pdf]
  • Fatemeh Sadat Saleh, Mohammad Sadegh Aliakbarian, Mathieu Salzmann, Lars Petersson, Jose M. Alvarez. ECCV'18
• (WC, HP) Penalizing Top Performers: Conservative Loss for Semantic Segmentation Adaptation [pdf]
  • Xinge Zhu, Hui Zhou, Ceyuan Yang, Jianping Shi, Dahua Lin. ECCV'18
• (WC, HP) Unsupervised Domain Adaptation for Semantic Segmentation via Class-Balanced Self-Training [pdf]
  • Yang Zou, Zhiding Yu, B.V.K. Vijaya Kumar, Jinsong Wang. ECCV'18

• AdaDepth: Unsupervised Content Congruent Adaptation for Depth Estimation [pdf]
  • Jogendra Nath Kundu, Phani Krishna Uppala, Anuj Pahuja, R. Venkatesh Babu. CVPR'18
• Real-Time Monocular Depth Estimation Using Synthetic Data With Domain Adaptation via Image Style Transfer [pdf]
  • Amir Atapour-Abarghouei, Toby P. Breckon. CVPR'18

• Multi-Evidence Filtering and Fusion for Multi-Label Classification, Object Detection and Semantic Segmentation Based on Weakly Supervised Learning [pdf]
  • Weifeng Ge, Sibei Yang, Yizhou Yu. CVPR'18
• Weakly-Supervised Semantic Segmentation by Iteratively Mining Common Object Features [pdf]
  • Xiang Wang, Shaodi You, Xi Li, Huimin Ma. CVPR'18
• Bootstrapping the Performance of Webly Supervised Semantic Segmentation [pdf]
  • Tong Shen, Guosheng Lin, Chunhua Shen, Ian Reid. CVPR'18
• On the Importance of Label Quality for Semantic Segmentation [pdf]
  • Aleksandar Zlateski, Ronnachai Jaroensri, Prafull Sharma, Frédo Durand. CVPR'18
• Normalized Cut Loss for Weakly-supervised CNN Segmentation [pdf]
  • Meng Tang, Abdelaziz Djelouah, Federico Perazzi, Yuri Boykov, Christopher Schroers. CVPR'18
• Weakly Supervised Instance Segmentation using Class Peak Response [pdf]
  • Yanzhao Zhou, Yi Zhu, Qixiang Ye, Qiang Qiu, Jianbin Jiao. CVPR'18
• Learning Pixel-level Semantic Affinity with Image-level Supervision for Weakly Supervised Semantic Segmentation [pdf]
  • Jiwoon Ahn, Suha Kwak. CVPR'18
• Instance Embedding Transfer to Unsupervised Video Object Segmentation [pdf]
  • Siyang Li, Bryan Seybold, Alexey Vorobyov, Alireza Fathi, Qin Huang, C.-C. Jay Kuo. CVPR'18
• Weakly-Supervised Semantic Segmentation Network with Deep Seeded Region Growing [pdf]
  • Zilong Huang, Xinggang Wang, Jiasi Wang, Wenyu Liu, Jingdong Wang. CVPR'18

• DARLA: Improving Zero-Shot Transfer in Reinforcement Learning [pdf]
  • Irina Higgins, Arka Pal, Andrei A. Rusu, Loic Matthey, Christopher P Burgess, Alexander Pritzel, Matthew Botvinick, Charles Blundell, Alexander Lerchner. ICML'17
• Learning to Imagine Manipulation Goals for Robot Task Planning [pdf]
  • Chris Paxton, Kapil Katyal, Christian Rupprecht, Raman Arora, Gregory D. Hager. arXiv'17
• (Stanley)Hierarchical and Interpretable Skill Acquisition in Multi-task Reinforcement Learning [pdf]
  • Tianmin Shu, Caiming Xiong, Richard Socher. ICLR'18
• (WC) Learning Robust Rewards with Adverserial Inverse Reinforcement Learning [pdf]
  • Justin Fu, Katie Luo, Sergey Levine. ICLR'18
• (WC) Adapting Deep Visuomotor Representations with Weak Pairwise Constraints [pdf] [ppt]
  • Eric Tzeng, Coline Devin, Judy Hoffman, Chelsea Finn, Pieter Abbeel, Sergey Levine, Kate Saenko, Trevor Darrell. WAFR'16
• Virtual to Real Reinforcement Learning for Autonomous Driving
  • Y You, X Pan, Z Wang, C Lu. arXiv'17
• From virtual demonstration to real-world manipulation using LSTM and MDN [pdf]
  • Rouhollah Rahmatizadeh, Pooya Abolghasemi, Aman Behal, Ladislau Bölöni. AAAI'18
• (HP) Bridging the Gap Between Simulation and Reality [pdf]
  • Josiah P. Hanna
• Grounded Action Transformation for Robot Learning in Simulation [pdf]
  • JP Hanna, P Stone. AAAI'17
• (BS)Learning to Navigate in Cities Without a Map [pdf] [ppt]
  • DeepMind. arXiv'18

• (HP) Transfer from Simulation to Real World through Learning Deep Inverse Dynamics Model [pdf] [slides]
  • Paul Christiano, Zain Shah, Igor Mordatch, Jonas Schneider, Trevor Blackwell, Joshua Tobin, Pieter Abbeel, Wojciech Zaremba. arXiv'16

• (HP) Domain Randomization for Transferring Deep Neural Networks from Simulation to the Real World [pdf]
  • Josh Tobin, Rachel Fong, Alex Ray, Jonas Schneider, Wojciech Zaremba, Pieter Abbeel. IROS'17

• (Stanley)Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation [pdf]
  • Tejas D. Kulkarni, Karthik R. Narasimhan, Ardavan Saeedi, Joshua B. Tenenbaum. NIPS'16
• Learning an Embedding Space for Transferable Robot Skills [pdf]
  • Karol Hausman, Jost Tobias Springenberg, Ziyu Wang, Nicolas Heess, Martin Riedmiller. ICLR'18

• Awesome meta-learning [link]
• Meta Learning Shared Hierachies [pdf]
  • Kevin Frans, Jonathan Ho, Xi Chen, Pieter Abbeel, John Schulman. ICLR'18
• (WC) Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks [pdf] [ppt]
  • Chelsea Finn, Pieter Abbeel, Sergey Levine. ICML'17
• (Stefanie) Prototypical Networks for Few-shot Learning [pdf]
  • Jake Snell, Kevin Swersky, Richard S. Zemel. arXiv'17
• (Stefanie) Meta-Learning for Semi-Supervised Few-Shot Classification [pdf]
  • Mengye Ren, Eleni Triantafillou, Sachin Ravi, Jake Snell, Kevin Swersky, Joshua B. Tenenbaum, Hugo Larochelle, Richard S. Zemel. ICLR'18
• Learning to learn by gradient descent by gradient descent [pdf]
  • Marcin Andrychowicz, Misha Denil, Sergio Gomez, Matthew W. Hoffman, David Pfau, Tom Schaul, Brendan Shillingford, Nando de Freitas. arXiv'16

• Deep Metric Learning with Hierarchical Triplet Loss [pdf]
  • Weifeng Ge, Weilin Huang, Dengke Dong, Matthew R. Scott. ECCV'18
• (WC) An Adversarial Approach to Hard Triplet Generation [pdf]
  • Yiru Zhao, Zhongming Jin, Guo-jun Qi, Hongtao Lu, Xian-sheng Hua. ECCV'18
• (WC) Deep Adversarial Metric Learning [pdf]
  • Yueqi Duan, Wenzhao Zheng, Xudong Lin, Jiwen Lu, Jie Zhou. CVPR'18
• (HP) Virtual Class Enhanced Discriminative Embedding Learning [pdf]
  • Binghui Chen, Weihong Deng, Haifeng Shen. NIPS'18
• (HP) Unsupervised Feature Learning via Non-Parametric Instance-level Discrimination [pdf]
  • Zhirong Wu, Yuanjun Xiong, Stella Yu, Dahua Lin. CVPR'18
• Deep Metric Learning with Angular Loss [pdf]
  • Jian Wang, Feng Zhou, Shilei Wen, Xiao Liu, Yuanqing Lin. ICCV'17
• Significance of Softmax-based Features in Comparison to Distance Metric Learning-based Features [pdf]
  • Shota Horiguchi, Daiki Ikami, Kiyoharu Aizawa. ArXiv'17
• Deep Metric Learning via Facility Location [pdf]
  • Hyun Oh Song, Stefanie Jegelka, Vivek Rathod, Kevin Murphy. CVPR'17
• Metric Learning with Adaptive Density Discrimination [pdf]
  • Rippel, Oren and Paluri, Manohar and Dollar, Piotr and Bourdev, Lubomir. ICLR'16

• Learning Invariant Feature Spaces to Transfer Skills with Reinforcement Learning [pdf]
  • Abhishek Gupta, Coline Devin, YuXuan Liu, Pieter Abbeel, Sergey Levine. ICLR'17
• Improving Deep Reinforcement Learning with Knowledge Transfer [pdf]
  • Ruben Glatt, Anna Helena Reali Costa. AAAI'17
• Towards Knowledge Transfer in Deep Reinforcement Learning [pdf]
  • Ruben Glatt, Felipe Leno da Silva, and Anna Helena Reali Costa.
• Pose-Robust Face Recognition via Deep Residual Equivariant Mapping [pdf]
  • Kaidi Cao, Yu Rong, Cheng Li, Xiaoou Tang, Chen Change Loy. CVPR'18
• (BS) Simultaneous Deep Transfer Across Domains and Tasks [pdf] [ppt]
  • Eric Tzeng, Judy Hoffman, Trevor Darrell, Kate Saenko. ICCV'15
• How transferable are features in deep neural networks? [pdf]
  • Jason Yosinski, Jeff Clune, Yoshua Bengio, Hod Lipson. NIPS'14
• (BS) Partial Transfer Learning With Selective Adversarial Networks. [pdf]
  • Zhangjie Cao, Mingsheng Long, Jianmin Wang, Michael I. Jordan. CVPR'18
• (HP) Taskonomy: Disentangling Task Transfer Learning. [pdf]
  • Amir Zamir, Alexander Sax, William Shen, Leonidas Guibas, Jitendra Malik, Silvio Savarese. CVPR'18-oral
• Unsupervised Cross-dataset Person Re-identification by Transfer Learning of Spatial-Temporal Patterns [pdf]
  • Jianming Lv, Weihang Chen, Qing Li, Can Yang. CVPR'18
• Learning Transferable Architectures for Scalable Image Recognition [pdf]
  • Barret Zoph, Vijay Vasudevan, Jonathon Shlens, Quoc V. Le. CVPR'18-oral
• Deep Cross-media Knowledge Transfer [pdf]
  • Xin Huang, Yuxin Peng. CVPR'18-oral
• Feature Space Transfer for Data Augmentation [pdf]
  • Bo Liu, Mandar Dixit, Roland Kwitt, Nuno Vasconcelos. CVPR'18-oral
• Large Scale Fine-Grained Categorization and Domain-Specific Transfer Learning [pdf]
  • Yin Cui, Yang Song, Chen Sun, Andrew Howard, Serge Belongie. CVPR'18
• Distant Domain Transfer Learning [pdf]
  • Ben Tan, Yu Zhang, Sinno Jialin Pan, Qiang Yang. AAAI'17

• (WC) Matching Networks for One Shot Learning [pdf]
  • Oriol Vinyals, Charles Blundell, Tim Lillicrap, koray kavukcuoglu, Daan Wierstra. NIPS'16
• (WC) Learning to Compare Relation Network for Few Shot Learning [pdf]
  • Flood Sung, Yongxin Tang, Li Zhang, Tao Xiang, Philip H.S. Torr, Timothy M. Hospedales
• Optimization as a Model for Few-Shot Learning [pdf]
  • Sachin Ravi, Hugo Larochelle. ICLR'17
• (HP) Siamese Neural Networks for One-shot Image Recognition [pdf]
  • Koch, Gregory, Richard Zemel, and Ruslan Salakhutdinov. ICML workshop'15
• Generative Adversarial Residual Pairwise Networks for One Shot Learning [pdf]
  • Akshay Mehrotra, Ambedkar Dukkipati. arXiv'17
• Few-Shot Learning Through an Information Retrieval Lens [pdf]
  • Eleni Triantafillou, Richard Zemel, Raquel Urtasun. NIPS'17

• (HP) Zero-Shot Visual Recognition using Semantics-Preserving Adversarial Embedding Networks [pdf]
  • Long Chen, Hanwang Zhang, Jun Xiao, Wei Liu, Shih-Fu Chang. CVPR'18
• (HP) Transductive Unbiased Embedding for Zero-Shot Learning [pdf]
  • Jie Song, Chengchao Shen, Yezhou Yang, Yang Liu, Mingli Song. CVPR'18
• (WC) Preserving Semantic Relations for Zero-Shot Learning [pdf]
  • Yashas Annadani, Soma Biswas. CVPR'18
• Generalized Zero-Shot Learning with Deep Calibration Network [pdf]
  • Shichen Liu, Mingsheng Long, Jianmin Wang, Michael I. Jordan. NIPS'18
• (WC) Domain-Invariant Projection Learning for Zero-Shot Recognition [pdf]
  • An Zhao, Mingyu Ding, Jiechao Guan, Zhiwu Lu, Tao Xiang, Ji-Rong Wen. NIPS'18
• A Generative Adversarial Approach for Zero-Shot Learning from Noisy Texts [pdf]
  • Yizhe Zhu, Mohamed Elhoseiny, Bingchen Liu, Xi Peng, Ahmed Elgammal. CVPR'18
• (HP) Generalized Zero-Shot Learning via Synthesized Examples [pdf]
  • Vinay Kumar Verma, Gundeep Arora, Ashish Mishra, Piyush Rai. CVPR'18
• Feature Generating Networks for Zero-Shot Learning [pdf]
  • Yongqin Xian, Tobias Lorenz, Bernt Schiele, Zeynep Akata. CVPR'18
• Discriminative Learning of Latent Features for Zero-Shot Recognition [pdf]
  • Yan Li, Junge Zhang, Jianguo Zhang, Kaiqi Huang. CVPR'18
• Zero-shot Domain Adaptation without Domain Semantic Descriptors [pdf]
  • Atsutoshi Kumagai, Tomoharu Iwata. arXiv'18

• (HP) Shuffle-then-assemble learning object-agnostic visual relationship features [pdf]
  • Xu Yang, Hanwang Zhang, Jianfei Cai. CVPR'18
• (HP) Learning Robust Representations by Projecting Superficial Statistics Out [pdf]
  • Haohan Wang, Zexue He, Zachary C. Lipton, Eric P. Xing. ICLR'19
• Tushar_Nagarajan_Attributes_as_Operators_ECCV_2018_paper. [pdf]
  • Tushar Nagarajan, Kristen Grauman. ECCV'18

• Bootstrapping with models: Confidence intervals for off-policy evaluation [pdf]
  • Josiah P. Hanna, Peter Stone, and Scott Niekum. AAMAS'17

• Learning How to Self-Learn: Enhancing Self-Training Using Neural Reinforcement Learning [pdf]
  • Chenhua Chen, Yue Zhang. arXiv'18
• A SELF-TRAINING METHOD FOR SEMI-SUPERVISED GANS [paf]
  • Alan Do-Omri, Dalei Wu & Xiaohua Liu. arXiv'17
• Domain Adaptation for Learning from Label Proportions Using Self-Training [pdf]
  • Ehsan Mohammady Ardehaly, Aron Culotta. IJCAI'16

• Closing the Simulation-to-Reality Gap for Deep Robotic Learning [link]
  • Google, 2017.

• Vision Meets Drones: A Challenge [pdf]
  • Pengfei Zhu, Longyin Wen, Xiao Bian, Haibing Ling, Qinghua Hu. arXiv'18

• Unsupervised Deep Embedding for Clustering Analysis [pdf][slides]
  • Junyuan Xie, Ross Girshick, Ali Farhadi. ICML'16
• Deep divergence-based clustering [pdf]
  • M. Kampffmeyer, S. Løkse, F. M. Bianchi, L. Livi, A.-B. Salberg and R. Jenssen. MLSP'17

• Decorrelated Batch Normalization [pdf]
  • Lei Huang, Dawei Yang, Bo Lang, Jia Deng. CVPR'18
• Recurrent Environment Simulators [pdf]
  • Silvia Chiappa, Sébastien Racaniere, Daan Wierstra, Shakir Mohamed. arXiv'17
• (BS) Explaining How a Deep Neural Network Trained with End-to-End Learning Steers a Car [pdf] [ppt]
  • Mariusz Bojarski, Philip Yeres, Anna Choromanska, Krzysztof Choromanski, Bernhard Firner, Lawrence Jackel, Urs Muller. arXiv'17
• (HP) Generating a Fusion Image: One's Identity and Another's Shape [pdf]
  • Donggyu Joo, Doyeon Kim, Junmo Kim. CVPR'18
• Disentangling Structure and Aesthetics for Style-Aware Image Completion [pdf]
  • Andrew Gilbert, John Collomosse, Hailin Jin, Brian Price. CVPR'18
• (HP) Self-Attention Generative Adversarial Networks [pdf]
  • Han Zhang, Ian Goodfellow, Dimitris Metaxas, Augustus Odena. ArXiv'18
• OLE: Orthogonal low-rank embedding, a plug and play geometric loss for deep learning
  • Lezama, Jos{'e} and Qiu, Qiang and Mus{'e}, Pablo and Sapiro, Guillermo. CVPR'18
• Deep cost-sensitive and order-preserving feature learning for cross-population age estimation. [pdf]
  • Kai Li, Junliang Xing, Chi Su, Weiming Hu, Yundong Zhang, Stephen Maybank. CVPR'18
• Learning superpixels with segmentation-aware affinity loss [pdf]
  • Wei-Chih Tu, Ming-Yu Liu, Varun Jampani, Deqing Sun, Shao-Yi Chien, Ming-Hsuan Yang, and Jan Kautz. CVPR'18
• *Multi-Image Semantic Matching by Mining Consistent Features [pdf]
  • Qianqian Wang, Xiaowei Zhou, Kostas Daniilidis. CVPR'18
• A Two-Step Disentanglement Method [pdf]
  • Naama Hadad, Lior Wolf, Moni Shahar. CVPR'18
• A Generative Adversarial Approach for Zero-Shot Learning from Noisy Texts [pdf]
  • Yizhe Zhu, Mohamed Elhoseiny, Bingchen Liu, Xi Peng, Ahmed Elgammal. CVPR'18
• *Transductive Unbiased Embedding for Zero-Shot Learning [pdf]
  • Jie Song, Chengchao Shen, Yezhou Yang, Yang Liu, Mingli Song. CVPR'18
• *Zero-Shot Visual Recognition using Semantics-Preserving Adversarial Embedding Networks [pdf]
  • Long Chen, Hanwang Zhang, Jun Xiao, Wei Liu, Shih-Fu Chang . CVPR'18
• Global versus Localized Generative Adversarial Nets [pdf]
  • Guo-Jun Qi, Liheng Zhang, Hao Hu, Marzieh Edraki, Jingdong Wang, Xian-Sheng Hua. CVPR'18
• Deep Adversarial Subspace Clustering [pdf]
  • Pan Zhou, Yunqing Hou, Jiashi Feng. CVPR'18
• Normalized Cut Loss for Weakly-supervised CNN Segmentation [pdf]
  • Meng Tang, Abdelaziz Djelouah, Federico Perazzi, Yuri Boykov, Christopher Schroers . CVPR'18
• Exploring Disentangled Feature Representation Beyond Face Identification [pdf]
  • Yu Liu, Fangyin Wei, Jing Shao, Lu Sheng, Junjie Yan, Xiaogang Wang. CVPR'18
• Decoupled Networks [pdf]
  • Weiyang Liu, Zhen Liu, Zhiding Yu, Bo Dai, Rongmei Lin, Yisen Wang, James M. Rehg, Le Song. CVPR'18
• *Zero-Shot Learning - The Good, the Bad and the Ugly [pdf]
  • Yongqin Xian, Bernt Schiele, Zeynep Akata. CVPR'17

• (JJ) Using Simulation and Domain Adaptation to Improve Efficiency of Deep Robotic Grasping [pdf]
  • Konstantinos Bousmalis, Alex Irpan, Paul Wohlhart, Yunfei Bai, Matthew Kelcey, Mrinal Kalakrishnan, Laura Downs, Julian Ibarz, Peter Pastor, Kurt Konolige, Sergey Levine, Vincent Vanhoucke. ICRA'18
• (BS) ADAPT: Zero-Shot Adaptive Policy Transfer for Stochastic Dynamical Systems [pdf] [ppt]
  • James HarMatching Networks for One Shot Learrison, Animesh Garg, Boris Ivanovic, Yuke Zhu, Silvio Savarese, Li Fei-Fei, Marco Pavone. arXiv'17 ISRR'17
• (Stanley)Transferring End-to-End Visuomotor Control from Simulation to Real World for a Multi-Stage Task [pdf]
  • Stephen James, Andrew J. Davison, Edward Johns. CoRL'17
• Using Simulation and Domain Adaptation to Improve Efficiency of Deep Robotic Grasping [pdf]
  • Konstantinos Bousmalis, Alex Irpan, Paul Wohlhart, Yunfei Bai, Matthew Kelcey, Mrinal Kalakrishnan, Laura Downs, Julian Ibarz, Peter Pastor, Kurt Konolige, Sergey Levine, Vincent Vanhoucke
• (JJ) Modular Continual Learning in a Unified Visual Environment [pdf]
  • Kevin T. Feigelis, Blue Sheffer, Daniel L. K. Yamins. ICLR'18
• (HP) Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments [pdf] [slides]
  • Maruan Al-Shedivat, Trapit Bansal, Yura Burda, Ilya Sutskever, Igor Mordatch, Pieter Abbeel. ICLR'18 Oral
• (WC) Recasting Gradient-Based Meta-Learning as Hierarchical Bayes [pdf]
  • Erin Grant, Chelsea Finn, Sergey Levine, Trevor Darrell, Thomas Griffiths. ICLR'18
• (BS) Universal Agent for Disentangling Environments and Tasks [pdf] [ppt]
  • Jiayuan Mao, Honghua Dong, Joseph J. Lim. ICLR'18