Recommended Papers

• The goal of this document is to provide a reading list for Deep Learning in Computer Vision Field.

Recommended Links

• Deep Learning Paper Reading Roadmap from songrotek

  If you are a newcomer to the Deep Learning area, the first question you may have is "Which paper should I start reading from?"

  Here is a reading roadmap of Deep Learning papers! link

• Deep-Learning-Paper list from sbrugman

  Deep Learning Papers by task! link

Paper Collections

• CVPR 2017 papers related to Attention Model
• Paper List for Instance Aware Tasks

Topics Concerned

• Salient Object Detection
• Visual Object Tracking
• Object Detection
• Object Localization
• Semantic Segmentation and Scene Parsing
• Edge Detection
• Pose Estimation
• Super Resolution
• Image Classification
• Others

Papers

Paper list.

Salient Object Detection

No.	Figure	Title	Authors	Pub.	Links
1		Visual Saliency Based on Multiscale Deep Features	Guanbin Li, Yizhou Yu	CVPR 2015	project page
2		Saliency Detection by Multi-context Deep Learning	Rui Zhao, Wanli Ouyang, Hongsheng Li, Xiaogang Wang	CVPR 2015	paper code
3		Deep Networks for Saliency Detection via Local Estimation and Global Search	Lijun Wang, Huchuan Lu, Xiang Ruan, Ming-Hsuan Yang	CVPR 2015	paper code
4		DHSNet: Deep Hierarchical Saliency Network for Salient Object Detection	Nian Liu, Junwei Han	CVPR 2016	paper Google Drive Baidu Yun ⭐
5		Deep Contrast Learning for Salient Object Detection	Guanbin Li, Yizhou Yu	CVPR 2016	project page
6		Saliency Unified: A Deep Architecture for Simultaneous Eye Fixation Prediction and Salient Object Segmentation	Srinivas S S Kruthiventi, Vennela Gudisa, Jaley H Dholakiya and R. Venkatesh Babu	CVPR 2016	project page
7		Deep Saliency with Encoded Low level Distance Map and High Level Features	Gayoung Lee, Yu-Wing Tai, Junmo Kim	CVPR 2016	paper code
8		Recurrent Attentional Networks for Saliency Detection	Jason Kuen, Zhenhua Wang, Gang Wang	CVPR 2016	paper
9		DeepSaliency: Multi-Task Deep Neural Network Model for Salient Object Detection	Xi Li, Liming Zhao, Lina Wei, Ming-Hsuan Yang, Fei Wu, Yueting Zhuang, Haibin Ling, Jingdong Wang	TIP 2016	project page
10		A Shape-Based Approach for Salient Object Detection Using Deep Learning	Jongpil Kim, Vladimir Pavlovic	ECCV 2016	paper Pre-computed Maps
11		Saliency Detection with Recurrent Fully Convolutional Networks	Linzhao Wang, Lijun Wang, Huchuan Lu, Pingping Zhang, Xiang Ruan	ECCV 2016	paper code
12		Deeply Supervised Salient Object Detection with Short Connections	Qibin Hou, Ming-Ming Cheng, Xiaowei Hu, Ali Borji, Zhuowen Tu, Philip Torr	CVPR 2017	paper github ⭐
13		Non-Local Deep Features for Salient Object Detection	Zhiming Luo, Akshaya Mishra , Andrew Achkar , Justin Eichel , Shaozi Li , Pierre-Marc.Jodoin	CVPR 2017	project page
14		Instance-Level Salient Object Segmentation	Guanbin Li, Yuan Xie, Liang Lin, Yizhou Yu	CVPR 2017	paper
15		Learning to Detect Salient Objects with Image-level Supervision	Lijun Wang, Huchuan Lu, Yifan Wang, Mengyang Feng, Dong Wang, Baocai Yin , Xiang Ruan	CVPR 2017	paper github
16		Deep Level Sets for Salient Object Detection	Ping Hu, Bing Shuai, Jun Liu, Gang Wang	CVPR 2017	paper
17		Learning Uncertain Convolutional Features for Accurate Saliency Detection	Pingping Zhang, Dong Wang, Huchuan Lu, Hongyu Wang, Baocai Yin	ICCV 2017	paper github
18		Amulet: Aggregating Multi-level Convolutional Features for Salient Object Detection	Pingping Zhang, Dong Wang, Huchuan Lu, Hongyu Wang, Xiang Ruan	ICCV 2017	paper github

Visual Object Tracking

Recommended Homepage---OTB Results. This shares results for more recent trackers.

Object Detection

No.	Figure	Title	Authors	Pub.	Links
1		Rich feature hierarchies for accurate object detection and semantic segmentation	Ross Girshick, Jeff Donahue, Trevor Darrell, Jitendra Malik	CVPR 2014	paper github ⭐
2		Fast R-CNN	Ross Girshick	ICCV 2015	paper github ⭐
3		Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks	Shaoqing Ren, Kaiming He, Ross Girshick, Jian Sun	NIPS 2015	paper matlab python pytorch ⭐
4		Convolutional Feature Masking for Joint Object and Stuff Segmentation	Jifeng Dai, Kaiming He, Jian Sun	CVPR 2015	paper
5		Instance-aware Semantic Segmentation via Multi-task Network Cascades	Jifeng Dai, Kaiming He, Jian Sun	CVPR 2016	paper github ⭐
6		R-FCN: Object Detection via Region-based Fully Convolutional Networks	Jifeng Dai, Yi Li, Kaiming He, Jian Sun	NIPS 2016	paper github
7		Feature Pyramid Networks for Object Detection	Tsung-Yi Lin, Piotr Dollár, Ross Girshick, Kaiming He, Bharath Hariharan, and Serge Belongie	CVPR 2017	paper
8		Mask R-CNN	Kaiming He, Georgia Gkioxari, Piotr Dollár, Ross Girshick	ICCV 2017	paper ⭐
9		A-Fast-RCNN: Hard Positive Generation via Adversary for Object Detection	Xiaolong Wang, Abhinav Shrivastava, Abhinav Gupta	CVPR 2017	paper github ⭐
10		Multiple Instance Detection Network with Online Instance Classifier Refinement	Peng Tang, Xinggang Wang, Xiang Bai, Wenyu Liu	CVPR 2017	paper
11		R-FCN-3000 at 30fps: Decoupling Detection and Classification	Bharat Singh, Hengdou Li, Abhishek Sharma and Larry S. Davis	Tech Report	paper

Object Localization

No.	Figure	Title	Authors	Pub.	Links
1		Simultaneous Detection and Segmentation	Bharath Hariharan, Pablo Arbeláez, Ross Girshick, Jitendra Malik	ECCV 2014	paper ⭐
2		Deep Self-Taught Learning for Weakly Supervised Object Localization	Zequn Jie, Yunchao Wei, Xiaojie Jin, Jiashi Feng, Wei Liu	CVPR 2017	paper
3		Learning Detection with Diverse Proposals	Samaneh Azadi, Jiashi Feng, Trevor Darrell	CVPR 2017	paper
4		Two-Phase Learning for Weakly Supervised Object Localization	Dahun Kim, Donghyeon Cho, Donggeun Yoo, In So Kweon	ICCV 2017	paper
5		Soft Proposal Networks for Weakly Supervised Object Localization	Yi Zhu, Yanzhao Zhou, Qixiang Ye, Qiang Qiu and Jianbin Jiao	ICCV 2017	paper github

Semantic Segmentation and Scene Parsing

No.	Figure	Title	Authors	Pub.	Links
1		Fully Convolutional Networks for Semantic Segmentation	Jonathan Long, Evan Shelhamer, Trevor Darrell	CVPR 2015	paper ⭐
2		Learning to Segment Object Candidates	Pedro O. Pinheiro, Ronan Collobert, Piotr Dollar	NIPS 2015	paper
3		Learning to Refine Object Segments	Pedro O. Pinheiro , Tsung-Yi Lin , Ronan Collobert, Piotr Doll ́ar	arXiv 1603.08695	paper
4		Conditional Random Fields as Recurrent Neural Networks	Shuai Zheng, Sadeep Jayasumana, Bernardino Romera-Paredes, Vibhav Vineet, ZhiZhong Su, Dalong Du, Chang Huang, and Philip H. S. Torr	ICCV 2015	paper
5		Learning Deconvolution Network for Semantic Segmentation	Heonwoo Noh, Seunghoon Hong, Bohyung Han	ICCV 2015	paper
6		Instance-sensitive Fully Convolutional Networks	Jifeng Dai, Kaiming He, Yi Li, Shaoqing Ren, Jian Sun	ECCV 2016	paper
7		Laplacian Pyramid Reconstruction and Refinement for Semantic Segmentation	Golnaz Ghiasi, Charless C. Fowlkes	ECCV 2016	paper github
8		Attention to Scale: Scale-aware Semantic Image Segmentation	Liang-Chieh Chen, Yi Yang, Jiang Wang, Wei Xu	CVPR 2016	paper DeepLab ⭐
9		RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation	Guosheng Lin, Anton Milan, Chunhua Shen, Ian Reid	CVPR 2017	paper github
10		Pyramid Scene Parsing Network	Hengshuang Zhao, Jianping Shi, Xiaojuan Qi, Xiaogang Wang, Jiaya Jia	CVPR 2017	paper github
11		Dilated Residual Networks	Fisher Yu, Vladlen Koltun, Thomas Funkhouser	CVPR 2017	paper
12		Fully Convolutional Instance-aware Semantic Segmentation	Yi Li, Haozhi Qi, Jifeng Dai, Xiangyang Ji, Yichen Wei	CVPR 2017	paper github
13		Full-Resolution Residual Networks for Semantic Segmentation in Street Scenes	Tobias Pohlen, Alexander Hermans, Markus Mathias, Bastian Leibe	CVPR 2017	paper github
14		Object Region Mining with Adversarial Erasing: A Simple Classification toSemantic Segmentation Approach	Yunchao Wei, Jiashi Feng, Xiaodan Liang, Ming-Ming Cheng, Yao Zhao, Shuicheng Yan	CVPR 2017	paper ⭐
15		Not All Pixels Are Equal: Difficulty-Aware Semantic Segmentation via Deep Layer Cascade	Xiaoxiao Li, Ziwei Liu, Ping Luo, Chen Change Loy, Xiaoou Tang	CVPR 2017	paper
16		Semantic Segmentation with Reverse Attention	Qin Huang, Chunyang Xia, Wuchi Hao, Siyang Li, Ye Wang, Yuhang Song and C.-C. Jay Kuo	BMVC 2017	paper code
17		Predicting Deeper into the Future of Semantic Segmentation	Pauline Luc, Natalia Neverova, Camille Couprie, Jakob Verbeek and Yann LeCun	ICCV 2017	paper project page
18		Learning to Segment Every Thing	Ronghang Hu, Piotr Dollar, Kaiming He, Trevor Darrell, Ross Girshick	Tech Report	paper

Edge Detection

No.	Figure	Title	Authors	Pub.	Links
1		Holistically-Nested Edge Detection	Saining Xie, Zhuowen Tu	ICCV 2015	paper github ⭐
2		Richer Convolutional Features for Edge Detection	Yun Liu, Ming-Ming Cheng, Xiaowei Hu, Kai Wang, Xiang Bai	CVPR 2017	paper project page
3		CASENet: Deep Category-Aware Semantic Edge Detection	Zhiding Yu, Chen Feng, Ming-Yu Liu, Srikumar Ramalingam	CVPR 2017	paper

Pose Estimation

No.	Figure	Title	Authors	Pub.	Links
1		Stacked Hourglass Networks for Human Pose Estimation	Alejandro Newell, Kaiyu Yang, and Jia Deng	ECCV 2016	paper ⭐
2		Multi-Context Attention for Human Pose Estimation	Xiao Chu, Wei Yang, Wanli Ouyang, Cheng Ma, Alan L. Yuille, Xiaogang Wang	CVPR 2017	paper github

Super Resolution

No.	Figure	Title	Authors	Pub.	Links
1		Deep Laplacian Pyramid Networks for Fast and Accurate Super-Resolution	Wei-Sheng Lai, Jia-Bin Huang, Narendra Ahuja, Ming-Hsuan Yang	CVPR 2017	project page
2		Image Super-Resolution via Deep Recursive Residual Network	Ying Tai, Jian Yang, and Xiaoming Liu	CVPR 2017	paper github

Image Classification

No.	Figure	Title	Authors	Pub.	Links
1		Going Deeper with Convolutions	Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed	CVPR 2015	paper ⭐
2		Deep Residual Learning for Image Recognition	Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun	CVPR 2016 best	paper github ⭐
3		Residual Attention Network for Image Classification	Fei Wang, Mengqing Jiang, Chen Qian, Shuo Yang, Cheng Li, Honggang Zhang, Xiaogang Wang, Xiaoou Tang	CVPR 2017	paper github ⭐
4		Aggregated Residual Transformations for Deep Neural Networks	Saining Xie, Ross Girshick, Piotr Dollár, Zhuowen Tu, and Kaiming He	CVPR 2017	paper github
5		Densely Connected Convolutional Networks	Gao Huang, Zhuang Liu, Kilian Q. Weinberger	CVPR 2017 best	paper github ⭐
6		Deep Pyramidal Residual Networks	Dongyoon Han, Jiwhan Kim, Junmo Kim	CVPR 2017	paper github ⭐

Others

No.	Figure	Title	Authors	Pub.	Links
1		Object Skeleton Extraction in Natural Images by Fusing Scale-associated Deep Side Outputs	Wei Shen, Kai Zhao, Yuan Jiang, Yan Wang, Zhijiang Zhang, Xiang Bai	ICCV 2016	paper github
2		AnchorNet: A Weakly Supervised Network to Learn Geometry-sensitive Features For Semantic Matching	David Novotny, DianeLarlus, Andrea Vedaldi	CVPR 2017	paper
3		SRN：Side-output Residual Network for Object Symmetry Detection in the Wild	Wei Ke, Jie Chen, Jianbin Jiao, Guoying Zhao and Qixiang Ye	CVPR 2017	paper github ⭐
4		Quality Aware Network for Set to Set Recognition	Yu Liu, Junjie Yan, Wanli Ouyang	CVPR 2017	paper
5		Multi-Scale Continuous CRFs as Sequential Deep Networks for Monocular Depth Estimation	Dan Xu, Elisa Ricci, Wanli Ouyang, Xiaogang Wang, Nicu Sebe	CVPR 2017	paper github ⭐
6		Learning Cross-Modal Deep Representations for Robust Pedestrian Detection	Dan Xu, Wanli Ouyang, Elisa Ricci, Xiaogang Wang, Nicu Sebe	CVPR 2017	paper
7		Semi-Supervised Deep Learning for Monocular Depth Map Prediction	Yevhen Kuznietsov, Jörg Stückler, Bastian Leibe	CVPR 2017	paper
8		Detecting Visual Relationships with Deep Relational Networks	Bo Dai, Yuqi Zhang, Dahua Lin	CVPR 2017	paper github
9		Annotating Object Instances with a Polygon-RNN	Lluis Castrejon, Kaustav Kundu, Raquel Urtasun, Sanja Fidler	CVPR 2017	paper ⭐
10		Weakly Supervised Cascaded Convolutional Networks	Ali Diba, Vivek Sharma, Ali Pazandeh, Hamed Pirsiavash, Luc Van Gool	CVPR 2017	paper
11		Full Resolution Image Compression with Recurrent Neural Networks	George Toderici, Damien Vincent, Nick Johnston, Sung Jin Hwang, David Minnen, Joel Shor, Michele Covell	CVPR 2017	paper github
12		Few-Shot Object Recognition from Machine-Labeled Web Images	Zhongwen Xu, Linchao Zhu, Yi Yang	CVPR 2017	paper
13		UberNet: Training a `Universal' Convolutional Neural Network for Low-, Mid-, and High-Level Vision using Diverse Datasets and Limited Memory	Iasonas Kokkinos	CVPR 2017	paper code
14		Generating High-Quality Crowd Density Maps using Contextual Pyramid CNNs	Vishwanath A. Sindagi and Vishal M. Patel	ICCV 2017	paper
15		MemNet: A Persistent Memory Network for Image Restoration	Ying Tai, Jian Yang, Xiaoming Liu, Chunyan Xu	ICCV 2017	paper github
16		Data Distillation: Towards Omni-Supervised Learning	Ilija Radosavovic, Piotr Dollar, Ross Girshick, GeorgiaGkioxari and Kaiming He	Tech Report	paper
17		Non-local Neural Networks	Xiaolong Wang, Ross Girshick, Abhinav Gupta and Kaiming He	Tech Report	paper