本文档整理了目标检测中各种提案方法的相关资源，包括不同类型的提案生成算法、论文、教程等，并介绍了各方法的特点及应用场景。
awesome-object-proposals 
A curated list of object proposals resources for object detection.
This Blog From this link: https://github.com/caocuong0306/awesome-object-proposals
Table of Contents
Introduction
- A Seismic Shift in Object Detection by Piotr Dollár.
- Generating Object Proposals by Piotr Dollár.
Tutorials
Papers
Objectness Scoring
- Objectness [Project]
- Bogdan Alexe, Thomas Deselaers, and Vittorio Ferrari, What is an object?, CVPR, 2010.
- Bogdan Alexe, Thomas Deselaers, and Vittorio Ferrari, Measuring the Objectness of Image Windows, TPAMI, 2012.
- Rahtu [Project]
- Esa Rahtu, Juho Kannala, and Matthew Blaschko, Learning a Category Independent Object Detection Cascade, ICCV, 2011.
- Cascaded Ranking SVMs [Code]
- Ziming Zhang, Jonathan Warrell, and Philip H. S. Torr, Proposal generation for object detection using cascaded ranking SVMs, CVPR, 2011.
- Salient
- Jie Feng, Yichen Wei, Litian Tao, Chao Zhang, and Jian Sun, Salient Object Detection by Composition, ICCV, 2011.
- RandomizedSeeds
- Michael Van den Bergh, Gemma Roig, Xavier Boix, Santiago Manen, Luc Van Gool, Online Video SEEDS for Temporal Window Objectness, ICCV, 2013.
- BING [Project]
- Ming-Ming Cheng, Ziming Zhang, Wen-Yan Lin, and Philip Torr, BING: Binarized Normed Gradients for Objectness Estimation at 300fps, CVPR, 2014.
- CrackingBING
- Qiyang Zhao, Zhibin Liu, Baolin Yin, Cracking BING and Beyond, BMVC, 2014.
- BING++
- Ziming Zhang, Yun Liu, Tolga Bolukbasi, Ming-Ming Cheng, and Venkatesh Saligrama, BING++: A Fast High Quality Object Proposal Generator at 100fps, arXiv:1511.04511.
- Ziming Zhang, Xi Chen, Yanjun Zhu, Zhiguo Cao, Venkatesh Saligrama, and Philip H.S. Torr, Sequential Optimization for Efficient High-Quality Object Proposal Generation, arXiv:1511.04511v2.
- EdgeBoxes [Project] [Code]
- Piotr Dollár and C. Lawrence Zitnick, Edge Boxes: Locating Object Proposals from Edges, ECCV, 2014.
- ContourBox
- Cewu Lu , Shu Liu, Jiaya Jia and Chi-Keung Tang, Contour Box: Rejecting Object Proposals Without Explicit Closed Contours, ICCV, 2015.
Similarity Grouping
- CPMC [Project]
- Joao Carreira and Cristian Sminchisescu, Constrained Parametric Min-Cuts for Automatic Object Segmentation, CVPR, 2010.
- Joao Carreira and Cristian Sminchisescu, CPMC: Automatic Object Segmentation Using Constrained Parametric Min-Cuts, TPAMI, 2012.
- Endres [Project]
- Ian Endres and Derek Hoiem, Category Independent Object Proposals, ECCV, 2010.
- Ian Endres and Derek Hoiem, Category-Independent Object Proposals With Diverse Ranking, TPAMI, 2014.
- Selective Search [Project]
- Koen E. A. van de Sande, Jasper R. R. Uijlings, Theo Gevers, and Arnold W. M. Smeulders, Segmentation As Selective Search for Object Recognition, ICCV, 2011.
- Jasper R. R. Uijlings, Koen E. A. van de Sande, Theo Gevers, and Arnold W. M. Smeulders, Selective Search for Object Recognition, IJCV, 2013.
- ObjSal [Project]
- Kai-Yueh Chang, Tyng-Luh Liu, Hwann-Tzong, and Chen Shang-Hong Lai, Fusing Generic Objectness and Visual Saliency for Salient Object Detection, ICCV, 2011.
- RandomizedPrim [Project]
- Santiago Manen, Matthieu Guillaumin, and Luc Van Gool, Prime Object Proposals with Randomized Prim's Algorithm, ICCV, 2013.
- Rantalankila
- Pekka Rantalankila, Juho Kannala, and Esa Rahtu, Generating Object Segmentation Proposals Using Global and Local Search , CVPR, 2014.
- RIGOR [Project]
- Ahmad Humayun, Fuxin Li, and James M. Rehg, RIGOR: Reusing Inference in Graph Cuts for Generating Object Regions, CVPR, 2014.
- GOP [Project]
- Philipp Krähenbühl and Vladlen Koltun, Geodesic Object Proposals, ECCV, 2014.
- MCG [Project]
- Pablo Arbelaez, Jordi Pont-Tuset, Jonathan T. Barron, Ferran Marques, Jitendra Malik, Multiscale Combinatorial Grouping, CVPR, 2014.
- Jordi Pont-Tuset, Pablo Arbelaez, Jonathan T. Barron, Ferran Marques, Jitendra Malik, Multiscale Combinatorial Grouping for Image Segmentation and Object Proposal Generation, TPAMI, 2017.
Supervised Learning
- MultiBox [Project]
- Dumitru Erhan, Christian Szegedy, Alexander Toshev, and Dragomir Anguelov, Scalable Object Detection using Deep Neural Networks, CVPR, 2014.
- Christian Szegedy, Scott Reed, Dumitru Erhan, and Dragomir Anguelov, Scalable, High-Quality Object Detection, arXiv:1412.1441.
- DeepMask [Code]
- Pedro O. Pinheiro, Ronan Collobert and Piotr Dollár, Learning to Segment Object Candidates, NIPS, 2015.
- Mid-level Cues
- Tom Lee, Sanja Fidler, and Sven Dickinson, Learning to Combine Mid-level Cues for Object Proposal Generation, ICCV, 2015.
- LPO [Project]
- Philipp Krähenbühl and Vladlen Koltun, Learning to Propose Objects, CVPR, 2015.
- RPN [Project]
- Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun, Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks, NIPS, 2015.
- DeepProposal [Code]
- Amir Ghodrati, Ali Diba, Marco Pedersoli, Tinne Tuytelaars, and Luc Van Gool, DeepProposal: Hunting Objects by Cascading Deep Convolutional Layers, ICCV, 2015.
- 3DOP [Project]
- Xiaozhi Chen, Kaustav Kundu, Yukun Zhu, Andrew Berneshawi, Huimin Ma, Sanja Fidler, and Raquel Urtasun, 3D Object Proposals for Accurate Object Class Detection, NIPS, 2015.
- Mono3D [Project]
- Xiaozhi Chen, Kaustav Kundu, Ziyu Zhang, Huimin Ma, Sanja Fidler, and Raquel Urtasun, Monocular 3D Object Detection for Autonomous Driving, CVPR, 2016.
- HyperNet
- Tao Kong, Anbang Yao, Yurong Chen, and Fuchun Sun, HyperNet: Towards Accurate Region Proposal Generation and Joint Object Detection, CVPR, 2016.
- CRAFT [Project]
- Bin Yang, Junjie Yan, Zhen Lei, and Stan Z. Li, CRAFT Objects From Images, CVPR, 2016.
- AttractioNet [Project]
- Spyros Gidaris and Nikos Komodakis, Attend Refine Repeat: Active Box Proposal Generation via In-Out Localization, BMVC, 2016.
- SPOP-net
- Zequn Jie, Xiaodan Liang, Jiashi Feng, Wen Feng Lu, Eng Hock Francis Tay, and Shuicheng Yan, Scale-Aware Pixelwise Object Proposal Networks, TIP, 2016.
- FCN
- Zequn Jie, Wen Feng Lu, Siavash Sakhavi, Yunchao Wei, Eng Hock Francis Tay, and Shuicheng Yan, Object Proposal Generation with Fully Convolutional Networks, TCSVT, 2016.
- InstanceFCN
- Jifeng Dai, Kaiming He, Yi Li, Shaoqing Ren, and Jian Sun, Instance-Sensitive Fully Convolutional Networks, ECCV, 2016.
- MV3D [Project]
- Xiaozhi Chen, Huimin Ma, Ji Wan, Bo Li, and Tian Xia, Multi-View 3D Object Detection Network for Autonomous Driving, arxiv.1611.07759. 2016.
Hybrid / Part-based
- ShapeSharing [Project]
- Jaechul Kim and Kristen Grauman, Shape Sharing for Object Segmentation, ECCV, 2012.
- OOP [Project]
- Shengfeng He and Rynson W.H. Lau, Oriented Object Proposals, ICCV, 2015.
- Object Discovery [Project]
- Minsu Cho, Suha Kwak, Cordelia Schmid, and Jean Ponce, Unsupervised Object Discovery and Localization in the Wild: Part-based Matching with Bottom-up Region Proposals, CVPR, 2015.
- Adobe Boxes [Code]
- Authors, Adobe Boxes: Locating Object Proposals Using Object Adobes, TIP, 2016.
RGB-D
- MCG-D [Project]
- Saurabh Gupta, Ross Girshick, Pablo Arbeláez and Jitendra Malik, Learning Rich Features from RGB-D Images for Object Detection and Segmentation, ECCV, 2014.
- StereoObj [Dataset]
- Shao Huang, Weiqiang Wang, Shengfeng He, and Rynson W.H. Lau, Stereo Object Proposals, TIP, 2017.
- Elastic Edge Boxes
- Jing Liu, Tongwei Ren, Yuantian Wang, Sheng-Hua Zhong, Jia Bei, Shengchao Chen, Object proposal on RGB-D images via elastic edge boxes, Neurocomputing, 2017.
Re-ranking & Refinement
- MTSE [Project]
- Xiaozhi Chen, Huimin Ma, Xiang Wang, Zhichen Zhao, Improving Object Proposals with Multi-Thresholding Straddling Expansion, CVPR, 2015.
- Xiaozhi Chen, Huimin Ma, Chenzhuo Zhu, Xiang Wang, Zhichen Zhao, Boundary-aware box refinement for object proposal generation, Neurocomputing, 2017.
- DeepBox [Project]
- Weicheng Kuo, Bharath Hariharan, and Jitendra Malik, DeepBox: Learning Objectness with Convolutional Networks, ICCV, 2015.
- SharpMask [Code]
- Pedro O. Pinheiro, Tsung-Yi Lin, Ronan Collobert, and Piotr Dollár, Learning to Refine Object Segments, ECCV, 2016.
- DeepStereoOP
- Cuong C. Pham and Jae Wook Jeon, Robust Object Proposals Re-ranking for Object Detection in Autonomous Driving Using Convolutional Neural Networks, SPIC, 2017.
Spatio-Temporal
- STMOP [Project]
- Katerina Fragkiadaki, Pablo Arbelaez, Panna Felsen, and Jitendra Malik, Learning to Segment Moving Objects in Videos, CVPR, 2015.
Evaluation
- Hosang benchmark [Project] [Code]
- Jan Hosang, Rodrigo Benenson, and Bernt Schiele, How good are detection proposals, really?, BMVC, 2014.
- Jan Hosang, Rodrigo Benenson, Piotr Dollár, and Bernt Schiele, What makes for effective detection proposals?, TPAMI, 2016.
- Jordi Pont-Tuset and Luc Van Gool, Boosting Object Proposals: From Pascal to COCO, ICCV, 2015. [Project]
- Neelima Chavali, Harsh Agrawal, Aroma Mahendru, and Dhruv Batra, Object-Proposal Evaluation Protocol is 'Gameable', CVPR, 2016. [Project]
Low-Level Processing
- Felzenszwalb's segmentation [Project]
- Pedro F. Felzenszwalb and Daniel P. Huttenlocher, Efficient Graph-Based Image Segmentation, IJCV, 2004.
- SLIC Superpixels [Project]
- Radhakrishna Achanta, Appu Shaji, Kevin Smith, Aurelien Lucchi, Pascal Fua, and Sabine Süsstrunk, SLIC Superpixels Compared to State-of-the-art Superpixel Methods, TPAMI, 2012.
- Structured Edge Detection [Code]
- Piotr Dollár and C. Lawrence Zitnick, Structured Forests for Fast Edge Detection , ICCV, 2013.
Datasets
- PASCAL [Project]
- Mark Everingham, Luc Van Gool, Christopher K. I. Williams, John Winn, and Andrew Zisserman, The PASCAL Visual Object Classes (VOC) Challenge, IJCV, 2010.
- MS COCO [Project]
- Tsung-Yi Lin, Michael Maire, Serge Belongie, Lubomir Bourdev, Ross Girshick, James Hays, Pietro Perona, Deva Ramanan, C. Lawrence Zitnick, and Piotr Dollár, Microsoft COCO: Common Objects in Context, ECCV, 2014.
- ImageNet [Project]
- Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li and Li Fei-Fei, ImageNet: A Large-Scale Hierarchical Image Database, CVPR, 2009.
- NYU Depth Dataset [Project]
- Nathan Silberman, Pushmeet Kohli, Derek Hoiem, and Rob Fergus, Indoor Segmentation and Support Inference from RGBD Images, ECCV, 2012.
- KITTI [Project]
- Andreas Geiger and Philip Lenz and Raquel Urtasun, Are we ready for Autonomous Driving? The KITTI Vision Benchmark Suite, CVPR, 2012.
Object Detection
- R-FCN [Code][PyCode]
- Jifeng Dai, Yi Li, Kaiming He, Jian Sun, R-FCN: Object Detection via Region-based Fully Convolutional Networks, NIPS, 2016.
- SSD [Code]
- Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, Alexander C. Berg, SSD: Single Shot MultiBox Detector, ECCV, 2016.
- YOLO [Code]
- Joseph Redmon, Santosh Divvala, Ross Girshick, Ali Farhadi, You Only Look Once: Unified, Real-Time Object Detection, ECCV, 2016.
- Faster R-CNN [Code] [PyCode]
- Shaoqing Ren, Kaiming He, Ross Girshick, Jian Sun, Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks, NIPS, 2015.
- Fast R-CNN [Code]
- Ross Girshick, Fast R-CNN, ICCV, 2015.
- SPP [Code]
- Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun, Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition, ECCV, 2014.
- R-CNN [Code]
- Ross Girshick, Jeff Donahue, Trevor Darrell, Jitendra Malik, Rich feature hierarchies for accurate object detection and semantic segmentation, CVPR, 2014.
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