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Deep reinforcement learning for computer vision

Summarize some high light papers around the application of deep reinforcement learning in computer vision domain. The main reference for this survey:

A tutorial during CVPR 2019

A simple Summarization of papers from Github

Zhihu

Object localization and detection

[1] Juan C. Caicedo, Svetlana Lazebnik. Active Object Localization with Deep Reinforcement Learning. ICCV, 2015. [Paper]

[2] Zequn Jie, Xiaodan Liang, Jiashi Feng, Xiaojie Jin, Wen Feng Lu, Shuicheng Yan. Tree-Structured Reinforcement Learning for Sequential Object Localization. NIPS, 2016. [Paper]

[3] Yongming Rao, Dahua Lin, Jiwen Lu, and Jie Zhou. "Learning globally optimized object detector via policy gradient." CVPR. 2018. [Paper]

[4] Tianshui Chen, Zhouxia Wang, Guanbin Li, Liang Lin. Recurrent Attentional Reinforcement Learning for Multi-label Image Recognition. AAAI, 2018 [Paper]

Semantic Segmentation

[1] Zhenxin Wang, Sayan Sarcar, Jingxin Liu, Yilin Zheng, Xiangshi Ren. Outline Objects using Deep Reinforcement Learning. [Paper]

[2] Yunze Man, Yangsibo Huang, Junyi Feng, Xi Li, Fei Wu. Deep Q Learning Driven CT Pancreas Segmentation with Geometry-Aware U-Net. [Paper]

Visual Tracking

[1] James Supančič, III, Deva Ramanan, Tracking as Online Decision-Making: Learning a Policy From Streaming Videos With Reinforcement Learning, ICCV, 2017. [Paper]

[2] Liangliang Ren, Xin Yuan, Jiwen Lu, Ming Yang, and Jie Zhou. "Deep Reinforcement Learning with Iterative Shift for Visual Tracking." ECCV2018. [Paper]

[3] Yun, S., Choi, J., Yoo, Y., Yun, K., & Choi, J. Y. (2017, July). Action-Decision Networks for Visual Tracking with Deep Reinforcement Learning. CVPR2017. [Paper]

[4] Liangliang Ren, Jiwen Lu, Zifeng Wang, Qi Tian, and Jie Zhou. "Collaborative Deep Reinforcement Learning for Multi-object Tracking." ECCV2018. [Paper]

Visual Dialogue

[1] Abhishek Das, Satwik Kottur, José M. F. Moura, Stefan Lee, Dhruv Batra, earning Cooperative Visual Dialog Agents with Deep Reinforcement Learning, ICCV 2017. [Paper]

Human Behaviour Analysis

[1] Nicholas Rhinehart, Kris M. Kitani, First-Person Activity Forecasting With Online Inverse Reinforcement Learning, ICCV, 2017. [Paper]

[2] Tang, Yansong, Yi Tian, Jiwen Lu, Peiyang Li, and Jie Zhou. "Deep Progressive Reinforcement Learning for Skeleton-Based Action Recognition." CVPR2018 [[Paper]] http://openaccess.thecvf.com/content_cvpr_2018/papers/Tang_Deep_Progressive_Reinforcement_CVPR_2018_paper.pdf

Face Recognition and Hallucination

[1] Yongming Rao,Jiwen Lu, Jie Zhou. Attention-aware Deep Reinforcement Learning for Video Face Recognition, ICCV, 2017. [Paper]

[2] Qingxing Cao, Liang Lin, Yukai Shi, Xiaodan Liang, Guanbin Li.Attention-Aware Face Hallucination via Deep Reinforcement Learning. CVPR, 2017. [Paper]

Image Restoration

[1] Ke Yu, Chao Dong, Liang Lin, Chen Change Loy. Crafting a Toolchain for Image Restoration by Deep Reinforcement Learning. CVPR 2018. [Paper]

Video Summarization and Captioning

[1] Kaiyang Zhou, Yu Qiao, Tao Xiang. Deep Reinforcement Learning for Unsupervised Video Summarization with Diversity-Representativeness Reward. AAAI, 2018. [Project]

[2] Wang, Xin, et al. "Video captioning via hierarchical reinforcement learning." CVPR2018. [Paper]

DRL for Visual Relationship Detection

[1] Liang, Xiaodan, Lisa Lee, and Eric P. Xing. Deep variation-structured reinforcement learning for visual relationship and attribute detection. CVPR, 2017. [Paper]

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A summarization of high light papers around the application of deep reinforcement learning in computer vision domain. The main reference for this survey:

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