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Many modern object detectors demonstrate outstanding performances by using the mechanism of looking and thinking twice.
A real-time algorithm for signal analysis with the help of the wavelet transform
Matthias Holschneider, Richard Kronland-Martinet, Jean Morlet, and Ph Tchamitchian · 1989
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Neural mechanisms of selective visual attention
Robert Desimone and John Duncan · 1995
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Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
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Visual attention mediated by biased competition in extrastriate visual cortex
Robert Desimone · 1998
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Top-down and bottom-up mechanisms in biasing competition in the human brain
Diane M Beck and Sabine Kastner · 2009
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Overfeat: Integrated recognition, localization and detection using convolutional networks
Pierre Sermanet, David Eigen, Xiang Zhang, Michaël Mathieu, Rob Fergus, and Yann LeCun · 2013
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Simultaneous detection and segmentation
Bharath Hariharan, Pablo Arbeláez, Ross Girshick, 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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Look and think twice: Capturing top-down visual attention with feedback convolutional neural networks
Chunshui Cao, Xianming Liu, Yi Yang, Yinan Yu, Jiang Wang, Zilei Wang, Yongzhen Huang, Liang Wang, Chang Huang, Wei Xu, et al · 2015
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Semantic image segmentation with deep convolutional nets and fully connected crfs
Liang-Chieh Chen, George Papandreou, Iasonas Kokkinos, Kevin Murphy, and Alan L Yuille · 2015
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The pascal visual object classes challenge: A retrospective
Mark Everingham, SM Ali Eslami, Luc Van Gool, Christopher KI Williams, John Winn, and Andrew Zisserman · 2015
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Fast r-cnn
Ross Girshick · 2015
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Deeply-supervised nets
Chen-Yu Lee, Saining Xie, Patrick Gallagher, Zhengyou Zhang, and Zhuowen Tu · 2015
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Recurrent convolutional neural network for object recognition
Ming Liang and Xiaolin Hu · 2015
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Modeling local and global deformations in deep learning: Epitomic convolution, multiple instance learning, and sliding window detection
George Papandreou, Iasonas Kokkinos, and Pierre-Andre Savalle · 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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ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, Alexander C. Berg, and Li Fei-Fei · 2015
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A unified multi-scale deep convolutional neural network for fast object detection
Zhaowei Cai, Quanfu Fan, Rogerio S Feris, and Nuno Vasconcelos · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Deeply-recursive convolutional network for image super-resolution
Jiwon Kim, Jung Kwon Lee, and Kyoung Mu Lee · 2016
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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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Wide residual networks
Sergey Zagoruyko and Nikos Komodakis · 2016
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Neural architecture search with reinforcement learning
Barret Zoph and Quoc V Le · 2016
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Gated feedback refinement network for dense image labeling
Md Amirul Islam, Mrigank Rochan, Neil DB Bruce, and Yang Wang · 2017
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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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Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs
Liang-Chieh Chen, George Papandreou, Iasonas Kokkinos, Kevin Murphy, and Alan L Yuille · 2017
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Rethinking atrous convolution for semantic image segmentation
Liang-Chieh Chen, George Papandreou, Florian Schroff, and Hartwig Adam · 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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Runtime neural pruning
Ji Lin, Yongming Rao, Jiwen Lu, and Jie Zhou · 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.
Focal loss for dense object detection
Tsung-Yi Lin, Priya Goyal, Ross Girshick, Kaiming He, and Piotr Dollár · 2017
Cited alongside, same era.
Yolo9000: better, faster, stronger
Joseph Redmon and Ali Farhadi · 2017
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Image super-resolution via deep recursive residual network
Ying Tai, Jian Yang, and Xiaoming Liu · 2017
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Aggregated residual transformations for deep neural networks
Saining Xie, Ross Girshick, Piotr Dollár, Zhuowen Tu, and Kaiming He · 2017
Cited alongside, same era.
Cascade r-cnn: Delving into high quality object detection
Zhaowei Cai and Nuno Vasconcelos · 2018
Cited alongside, same era.
Scale-aware trident networks for object detection
Yanghao Li, Yuntao Chen, Naiyan Wang, and Zhaoxiang Zhang · 2019
Later among the works it cites.
Libra r-cnn: Towards balanced learning for object detection
Jiangmiao Pang, Kai Chen, Jianping Shi, Huajun Feng, Wanli Ouyang, and Dahua Lin · 2019
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Seamless scene segmentation
Lorenzo Porzi, Samuel Rota Bulo, Aleksander Colovic, and Peter Kontschieder · 2019
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Adaptis: Adaptive instance selection network
Konstantin Sofiiuk, Olga Barinova, and Anton Konushin · 2019
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Efficientdet: Scalable and efficient object detection
Mingxing Tan, Ruoming Pang, and Quoc V Le · 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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Masklab: Instance segmentation by refining object detection with semantic and direction features
Liang-Chieh Chen, Alexander Hermans, George Papandreou, Florian Schroff, Peng Wang, and Hartwig Adam · 2018
Cited alongside, same era.
Encoder-decoder with atrous separable convolution for semantic image segmentation
Liang-Chieh Chen, Yukun Zhu, George Papandreou, Florian Schroff, and Hartwig Adam · 2018
Cited alongside, same era.
Squeeze-and-excitation networks
Jie Hu, Li Shen, and Gang Sun · 2018
Cited alongside, same era.
Cornernet: Detecting objects as paired keypoints
Hei Law and Jia Deng · 2018
Cited alongside, same era.
Learning to fuse things and stuff
Jie Li, Allan Raventos, Arjun Bhargava, Takaaki Tagawa, and Adrien Gaidon · 2018
Cited alongside, same era.
Dynamic deep neural networks: Optimizing accuracy-efficiency trade-offs by selective execution
Lanlan Liu and Jia Deng · 2018
Cited alongside, same era.
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Wider or deeper: Revisiting the resnet model for visual recognition
Zifeng Wu, Chunhua Shen, and Anton Van Den Hengel · 2019
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Upsnet: A unified panoptic segmentation network
Yuwen Xiong, Renjie Liao, Hengshuang Zhao, Rui Hu, Min Bai, Ersin Yumer, and Raquel Urtasun · 2019
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Auto-fpn: Automatic network architecture adaptation for object detection beyond classification
Hang Xu, Lewei Yao, Wei Zhang, Xiaodan Liang, and Zhenguo Li · 2019
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Condconv: Conditionally parameterized convolutions for efficient inference
Brandon Yang, Gabriel Bender, Quoc V Le, and Jiquan Ngiam · 2019
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Deeperlab: Single-shot image parser
Tien-Ju Yang, Maxwell D Collins, Yukun Zhu, Jyh-Jing Hwang, Ting Liu, Xiao Zhang, Vivienne Sze, George Papandreou, and Liang-Chieh Chen · 2019
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Sognet: Scene overlap graph network for panoptic segmentation
Yibo Yang, Hongyang Li, Xia Li, Qijie Zhao, Jianlong Wu, and Zhouchen Lin · 2019
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M2det: A single-shot object detector based on multi-level feature pyramid network
Qijie Zhao, Tao Sheng, Yongtao Wang, Zhi Tang, Ying Chen, Ling Cai, and Haibin Ling · 2019
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Xingyi Zhou, Dequan Wang, and Philipp Krähenbühl · 2019
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Bottom-up object detection by grouping extreme and center points
Xingyi Zhou, Jiacheng Zhuo, and Philipp Krahenbuhl · 2019
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Feature selective anchor-free module for single-shot object detection
Chenchen Zhu, Yihui He, and Marios Savvides · 2019
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Deformable convnets v2: More deformable, better results
Xizhou Zhu, Han Hu, Stephen Lin, and Jifeng Dai · 2019
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D2det: Towards high quality object detection and instance segmentation
Jiale Cao, Hisham Cholakkal, Rao Muhammad Anwer, Fahad Shahbaz Khan, Yanwei Pang, and Ling Shao · 2020
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Naive-student: Leveraging semi-supervised learning in video sequences for urban scene segmentation
Liang-Chieh Chen, Raphael Gontijo Lopes, Bowen Cheng, Maxwell D. Collins, Ekin D. Cubuk, Barret Zoph, Hartwig Adam, and Jonathon Shlens · 2020
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Dynamic convolution: Attention over convolution kernels
Yinpeng Chen, Xiyang Dai, Mengchen Liu, Dongdong Chen, Lu Yuan, and Zicheng Liu · 2020
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Panoptic-deeplab: A simple, strong, and fast baseline for bottom-up panoptic segmentation
Bowen Cheng, Maxwell D Collins, Yukun Zhu, Ting Liu, Thomas S Huang, Hartwig Adam, and Liang-Chieh Chen · 2020
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Augfpn: Improving multi-scale feature learning for object detection
Chaoxu Guo, Bin Fan, Qian Zhang, Shiming Xiang, and Chunhong Pan · 2020
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Sp-nas: Serial-to-parallel backbone search for object detection
Chenhan Jiang, Hang Xu, Wei Zhang, Xiaodan Liang, and Zhenguo Li · 2020
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Learning from noisy anchors for one-stage object detection
Hengduo Li, Zuxuan Wu, Chen Zhu, Caiming Xiong, Richard Socher, and Larry S Davis · 2020
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Unifying training and inference for panoptic segmentation
Qizhu Li, Xiaojuan Qi, and Philip HS Torr · 2020
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Cbnet: A novel composite backbone network architecture for object detection
Yudong Liu, Yongtao Wang, Siwei Wang, TingTing Liang, Qijie Zhao, Zhi Tang, and Haibin Ling · 2020
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Revisiting the sibling head in object detector
Guanglu Song, Yu Liu, and Xiaogang Wang · 2020
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Axial-deeplab: Stand-alone axial-attention for panoptic segmentation
Huiyu Wang, Yukun Zhu, Bradley Green, Hartwig Adam, Alan Yuille, and Liang-Chieh Chen · 2020
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Nas-fcos: Fast neural architecture search for object detection
Ning Wang, Yang Gao, Hao Chen, Peng Wang, Zhi Tian, Chunhua Shen, and Yanning Zhang · 2020
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Scale-equalizing pyramid convolution for object detection
Xinjiang Wang, Shilong Zhang, Zhuoran Yu, Litong Feng, and Wayne Zhang · 2020
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Rethinking classification and localization for object detection
Yue Wu, Yinpeng Chen, Lu Yuan, Zicheng Liu, Lijuan Wang, Hongzhi Li, and Yun Fu · 2020
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