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Pedestrian detection in crowd scenes poses a challenging problem due to the heuristic defined mapping from anchors to pedestrians and the conflict between NMS and highly overlapped pedestrians.
Pedestrian detection: An evaluation of the state of the art
Piotr Dollar, Christian Wojek, Bernt Schiele, and Pietro Perona · 2011
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Rich feature hierarchies for accurate object detection and semantic segmentation
Ross Girshick, Jeff Donahue, Trevor Darrell, and Jitendra Malik · 2014
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Microsoft coco: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick · 2014
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Fast r-cnn
Ross Girshick · 2015
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Spatial pyramid pooling in deep convolutional networks for visual recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2015
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Faster r-cnn: Towards real-time object detection with region proposal networks
Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun · 2015
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Ssd: Single shot multibox detector
Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, and Alexander C Berg · 2016
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You only look once: Unified, real-time object detection
Joseph Redmon, Santosh Divvala, Ross Girshick, and Ali Farhadi · 2016
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End-to-end people detection in crowded scenes
Russell Stewart, Mykhaylo Andriluka, and Andrew Y Ng · 2016
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How far are we from solving pedestrian detection?
Shanshan Zhang, Rodrigo Benenson, Mohamed Omran, Jan Hosang, and Bernt Schiele · 2016
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Soft-nms–improving object detection with one line of code
Navaneeth Bodla, Bharat Singh, Rama Chellappa, and Larry S Davis · 2017
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Deformable convolutional networks
Jifeng Dai, Haozhi Qi, Yuwen Xiong, Yi Li, Guodong Zhang, Han Hu, and Yichen Wei · 2017
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Mask r-cnn
Kaiming He, Georgia Gkioxari, Piotr Dollár, and Ross Girshick · 2017
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Feature pyramid networks for object detection
Tsung-Yi Lin, Piotr Dollár, Ross Girshick, Kaiming He, Bharath Hariharan, and Serge Belongie · 2017
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Focal loss for dense object detection
Tsung-Yi Lin, Priya Goyal, Ross Girshick, Kaiming He, and Piotr Dollár · 2017
Cited alongside, same era.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
Cited alongside, same era.
Citypersons: A diverse dataset for pedestrian detection
Shanshan Zhang, Rodrigo Benenson, and Bernt Schiele · 2017
Cited alongside, same era.
Softer-nms: Rethinking bounding box regression for accurate object detection
Yihui He, Xiangyu Zhang, Marios Savvides, and Kris Kitani · 2018
Cited alongside, same era.
Relation networks for object detection
Han Hu, Jiayuan Gu, Zheng Zhang, Jifeng Dai, and Yichen Wei · 2018
Cited alongside, same era.
Acquisition of localization confidence for accurate object detection
Borui Jiang, Ruixuan Luo, Jiayuan Mao, Tete Xiao, and Yuning Jiang · 2018
Nas-fpn: Learning scalable feature pyramid architecture for object detection
Golnaz Ghiasi, Tsung-Yi Lin, and Quoc V Le · 2019
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Mask scoring r-cnn
Zhaojin Huang, Lichao Huang, Yongchao Gong, Chang Huang, and Xinggang Wang · 2019
Later among the works it cites.
Adaptive nms: Refining pedestrian detection in a crowd
Songtao Liu, Di Huang, and Yunhong Wang · 2019
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High-level semantic feature detection: A new perspective for pedestrian detection
Wei Liu, Shengcai Liao, Weiqiang Ren, Weidong Hu, and Yinan Yu · 2019
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Mask-guided attention network for occluded pedestrian detection
Yanwei Pang, Jin Xie, Muhammad Haris Khan, Rao Muhammad Anwer, Fahad Shahbaz Khan, and Ling Shao · 2019
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Fcos: Fully convolutional one-stage object detection
Zhi Tian, Chunhua Shen, Hao Chen, and Tong He · 2019
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Cited alongside, same era.
Gradient harmonized single-stage detector
Buyu Li, Yu Liu, and Xiaogang Wang · 2018
Cited alongside, same era.
Learning efficient single-stage pedestrian detectors by asymptotic localization fitting
Wei Liu, Shengcai Liao, Weidong Hu, Xuezhi Liang, and Xiao Chen · 2018
Cited alongside, same era.
Crowdhuman: A benchmark for detecting human in a crowd
Shuai Shao, Zijian Zhao, Boxun Li, Tete Xiao, Gang Yu, Xiangyu Zhang, and Jian Sun · 2018
Cited alongside, same era.
Small-scale pedestrian detection based on topological line localization and temporal feature aggregation
Tao Song, Leiyu Sun, Di Xie, Haiming Sun, and Shiliang Pu · 2018
Cited alongside, same era.
Repulsion loss: Detecting pedestrians in a crowd
Xinlong Wang, Tete Xiao, Yuning Jiang, Shuai Shao, Jian Sun, and Chunhua Shen · 2018
Cited alongside, same era.
Occlusion-aware r-cnn: detecting pedestrians in a crowd
Shifeng Zhang, Longyin Wen, Xiao Bian, Zhen Lei, and Stan Z Li · 2018
Cited alongside, same era.
Later among the works it cites.
Xingyi Zhou, Dequan Wang, and Philipp Krähenbühl · 2019
Later among the works it cites.
Deformable convnets v2: More deformable, better results
Xizhou Zhu, Han Hu, Stephen Lin, and Jifeng Dai · 2019
Later among the works it cites.
End-to-end object detection with transformers
Nicolas Carion, Francisco Massa, Gabriel Synnaeve, Nicolas Usunier, Alexander Kirillov, and Sergey Zagoruyko · 2020
Closest in time.
Relational learning for joint head and human detection
Cheng Chi, Shifeng Zhang, Junliang Xing, Zhen Lei, Stan Z Li, and Xudong Zou · 2020
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Pedhunter: Occlusion robust pedestrian detector in crowded scenes
Cheng Chi, Shifeng Zhang, Junliang Xing, Zhen Lei, Stan Z Li, Xudong Zou, et al · 2020
Closest in time.
Nms by representative region: Towards crowded pedestrian detection by proposal pairing
Xin Huang, Zheng Ge, Zequn Jie, and Osamu Yoshie · 2020
Closest in time.
Beta r-cnn: Looking into pedestrian detection from another perspective
Zixuan Xu, Banghuai Li, Ye Yuan, and Anhong Dang · 2020
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Deformable detr: Deformable transformers for end-to-end object detection
Xizhou Zhu, Weijie Su, Lewei Lu, Bin Li, Xiaogang Wang, and Jifeng Dai · 2020
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