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We address the task of domain adaptation in object detection, where there is a domain gap between a domain with annotations (source) and a domain of interest without annotations (target).
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Karen Simonyan and Andrew Zisserman · 2014
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Yaroslav Ganin and Victor Lempitsky · 2015
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Learning transferable features with deep adaptation networks
Mingsheng Long, Yue Cao, Jianmin Wang, and Michael Jordan · 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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The cityscapes dataset for semantic urban scene understanding
Marius Cordts, Mohamed Omran, Sebastian Ramos, Timo Rehfeld, Markus Enzweiler, Rodrigo Benenson, Uwe Franke, Stefan Roth, and Bernt Schiele · 2016
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R-fcn: Object detection via region-based fully convolutional networks
Jifeng Dai, Yi Li, Kaiming He, and Jian Sun · 2016
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Domain-adversarial training of neural networks
Yaroslav Ganin, Evgeniya Ustinova, Hana Ajakan, Pascal Germain, Hugo Larochelle, François Laviolette, Mario Marchand, and Victor Lempitsky · 2016
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Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 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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Unsupervised domain adaptation with residual transfer networks
Mingsheng Long, Han Zhu, Jianmin Wang, and Michael I Jordan · 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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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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Deep transfer learning with joint adaptation networks
Mingsheng Long, Han Zhu, Jianmin Wang, and Michael I Jordan · 2017
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Joseph Redmon and Ali Farhadi · 2017
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Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results
Antti Tarvainen and Harri Valpola · 2017
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Adversarial discriminative domain adaptation
Eric Tzeng, Judy Hoffman, Kate Saenko, and Trevor Darrell · 2017
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Unpaired image-to-image translation using cycle-consistent adversarial networks
Jun-Yan Zhu, Taesung Park, Phillip Isola, and Alexei A Efros · 2017
Multi-adversarial faster-rcnn for unrestricted object detection
Zhenwei He and Lei Zhang · 2019
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A robust learning approach to domain adaptive object detection
Mehran Khodabandeh, Arash Vahdat, Mani Ranjbar, and William G Macready · 2019
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Self-training and adversarial background regularization for unsupervised domain adaptive one-stage object detection
Seunghyeon Kim, Jaehoon Choi, Taekyung Kim, and Changick Kim · 2019
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Diversify and match: A domain adaptive representation learning paradigm for object detection
Taekyung Kim, Minki Jeong, Seunghyeon Kim, Seokeon Choi, and Changick Kim · 2019
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Automatic adaptation of object detectors to new domains using self-training
Aruni RoyChowdhury, Prithvijit Chakrabarty, Ashish Singh, SouYoung Jin, Huaizu Jiang, Liangliang Cao, and Erik Learned-Miller · 2019
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Domain adaptive faster r-cnn for object detection in the wild
Yuhua Chen, Wen Li, Christos Sakaridis, Dengxin Dai, and Luc Van Gool · 2018
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Relation networks for object detection
Han Hu, Jiayuan Gu, Zheng Zhang, Jifeng Dai, and Yichen Wei · 2018
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Cross-domain weakly-supervised object detection through progressive domain adaptation
Naoto Inoue, Ryosuke Furuta, Toshihiko Yamasaki, and Kiyoharu Aizawa · 2018
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Megdet: A large mini-batch object detector
Chao Peng, Tete Xiao, Zeming Li, Yuning Jiang, Xiangyu Zhang, Kai Jia, Gang Yu, and Jian Sun · 2018
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Yolov3: An incremental improvement
Joseph Redmon and Ali Farhadi · 2018
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Semantic foggy scene understanding with synthetic data
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Strong-weak distribution alignment for adaptive object detection
Kuniaki Saito, Yoshitaka Ushiku, Tatsuya Harada, and Kate Saenko · 2019
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Zhiqiang Shen, Harsh Maheshwari, Weichen Yao, and Marios Savvides · 2019
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Adapting object detectors via selective cross-domain alignment
Xinge Zhu, Jiangmiao Pang, Ceyuan Yang, Jianping Shi, and Dahua Lin · 2019
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Harmonizing transferability and discriminability for adapting object detectors
Chaoqi Chen, Zebiao Zheng, Xinghao Ding, Yue Huang, and Qi Dou · 2020
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Adapting object detectors with conditional domain normalization
Peng Su, Kun Wang, Xingyu Zeng, Shixiang Tang, Dapeng Chen, Di Qiu, and Xiaogang Wang · 2020
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Exploring categorical regularization for domain adaptive object detection
Chang-Dong Xu, Xing-Ran Zhao, Xin Jin, and Xiu-Shen Wei · 2020
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ifan: Image-instance full alignment networks for adaptive object detection
Chenfan Zhuang, Xintong Han, Weilin Huang, and Matthew Scott · 2020
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Unbiased mean teacher for cross-domain object detection
Jinhong Deng, Wen Li, Yuhua Chen, and Lixin Duan · 2021
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Unbiased teacher for semi-supervised object detection
Yen-Cheng Liu, Chih-Yao Ma, Zijian He, Chia-Wen Kuo, Kan Chen, Peizhao Zhang, Bichen Wu, Zsolt Kira, and Peter Vajda · 2021
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Curriculum self-paced learning for cross-domain object detection
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