- The goal of this document is to provide a reading list for Deep Learning in Computer Vision Field.
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Deep Learning Paper Reading Roadmap
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
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Deep-Learning-Paper list from sbrugman
Deep Learning Papers by task!
link
- Salient Object Detection
- Visual Object Tracking
- Object Detection
- Object Localization
- Semantic Segmentation and Scene Parsing
- Edge Detection
- Pose Estimation
- Super Resolution
- Image Classification
- Others
Paper list.
No. | Figure | Title | Authors | Pub. | Links |
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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 |
17 | ![]() |
Amulet: Aggregating Multi-level Convolutional Features for Salient Object Detection | Pingping Zhang, Dong Wang, Huchuan Lu, Hongyu Wang, Xiang Ruan | ICCV 2017 | paper github |
Recommended Homepage---OTB Results. This shares results for more recent trackers.
No. | Figure | Title | Authors | Pub. | Links |
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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 |
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 |
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 |
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 |
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 |
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 |
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 ⭐ |
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 |