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Obtaining object response maps is one important step to achieve weakly-supervised semantic segmentation using image-level labels.
Semi-supervised learning by entropy minimization
Yves Grandvalet and Yoshua Bengio · 2005
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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The PASCAL Visual Object Classes Challenge 2010 (VOC2010) Results
M. Everingham, L. Van Gool, C. K. I. Williams, J. Winn, and A. Zisserman · 2010
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Semantic contours from inverse detectors
Bharath Hariharan, Pablo Arbeláez, Lubomir Bourdev, Subhransu Maji, and Jitendra Malik · 2011
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Efficient inference in fully connected crfs with gaussian edge potentials
Philipp Krahenbuhl and Vladlen Koltun · 2011
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Boxsup: Exploiting bounding boxes to supervise convolutional networks for semantic segmentation
Jifeng Dai, Kaiming He, and Jian Sun · 2015
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2015
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Weakly-and semi-supervised learning of a dcnn for semantic image segmentation
George Papandreou, Liang-Chieh Chen, Kevin Murphy, and Alan L Yuille · 2015
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Constrained convolutional neural networks for weakly supervised segmentation
Deepak Pathak, Philipp Krahenbuhl, and Trevor Darrell · 2015
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From image-level to pixel-level labeling with convolutional networks
Pedro O Pinheiro and Ronan Collobert · 2015
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What’s the point: Semantic segmentation with point supervision
Amy Bearman, Olga Russakovsky, Vittorio Ferrari, and Li Fei-Fei · 2016
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Liang-Chieh Chen, George Papandreou, Iasonas Kokkinos, Kevin Murphy, and Alan L Yuille · 2016
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Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Fully convolutional networks for semantic segmentation
Jonathan helhamer, Evan an Long and Trevor Darrell · 2016
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Seed, expand and constrain: Three principles for weakly-supervised image segmentation
Alexander Kolesnikov and Christoph H Lampert · 2016
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Scribblesup: Scribble-supervised convolutional networks for semantic segmentation
Di Lin, Jifeng Dai, Jiaya Jia, Kaiming He, and Jian Sun · 2016
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Semantic co-segmentation in videos
Yi-Hsuan Tsai, Guangyu Zhong, and Ming-Hsuan Yang · 2016
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Fisher Yu and Vladlen Koltun · 2016
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Guangyu Zhong, Yi-Hsuan Tsai, and Ming-Hsuan Yang · 2016
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Learning deep features for discriminative localization
Bolei Zhou, Aditya Khosla, Agata Lapedriza, Aude Oliva, and Antonio Torralba · 2016
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Discovering class-specific pixels for weakly-supervised semantic segmentation
Arslan Chaudhry, Puneet K Dokania, and Philip HS Torr · 2017
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Simple does it: Weakly supervised instance and semantic segmentation
A. Khoreva, R. Benenson, J. Hosang, M. Hein, and B. Schiele · 2017
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Regularizing neural networks by penalizing confident output distributions
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David Berthelot, Nicholas Carlini, Ian Goodfellow, Nicolas Papernot, Avital Oliver, and Colin A Raffel · 2019
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Ekin D Cubuk, Barret Zoph, Dandelion Mane, Vijay Vasudevan, and Quoc V Le · 2019
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Cian: Cross-image affinity net for weakly supervised semantic segmentation
Junsong Fan, Zhaoxiang Zhang, and Tieniu Tan · 2019
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Mixup as locally linear out-of-manifold regularization
Hongyu Guo, Yongyi Mao, and Richong Zhang · 2019
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Wei-Chih Hung, Varun Jampani, Sifei Liu, Pavlo Molchanov, Ming-Hsuan Yang, and Jan Kautz · 2019
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Integral object mining via online attention accumulation
Peng-Tao Jiang, Qibin Hou, Yang Cao, Ming-Ming Cheng, Yunchao Wei, and Hong-Kai Xiong · 2019
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Gabriel Pereyra, George Tucker, Jan Chorowski, Łukasz Kaiser, and Geoffrey Hinton · 2017
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Hide-and-seek: Forcing a network to be meticulous for weakly-supervised object and action localization
Krishna Kumar Singh and Yong Jae Lee · 2017
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Learning random-walk label propagation for weakly-supervised semantic segmentation
Paul Vernaza and Manmohan Chandraker · 2017
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Object region mining with adversarial erasing: A simple classification to semantic segmentation approach
Yunchao Wei, Jiashi Feng, Xiaodan Liang, Ming-Ming Cheng, Yao Zhao, and Shuicheng Yan · 2017
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Learning pixel-level semantic affinity with image-level supervision for weakly supervised semantic segmentation
Jiwoon Ahn and Suha Kwak · 2018
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Associating inter-image salient instances for weakly supervised semantic segmentation
Ruochen Fan, Qibin Hou, Ming-Ming Cheng, Gang Yu, Ralph R Martin, and Shi-Min Hu · 2018
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Self-erasing network for integral object attention
Qibin Hou, PengTao Jiang, Yunchao Wei, and Ming-Ming Cheng · 2018
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Jungbeom Lee, Eunji Kim, Sungmin Lee, Jangho Lee, and Sungroh Yoon · 2019
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Fast autoaugment
Sungbin Lim, Ildoo Kim, Taesup Kim, Chiheon Kim, and Sungwoong Kim · 2019
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Self-supervised difference detection for weakly-supervised semantic segmentation
Wataru Shimoda and Keiji Yanai · 2019
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Improved mixed-example data augmentation
Cecilia Summers and Michael J Dinneen · 2019
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On mixup training: Improved calibration and predictive uncertainty for deep neural networks
Sunil Thulasidasan, Gopinath Chennupati, Jeff Bilmes, Tanmoy Bhattacharya, and Sarah Michalak · 2019
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Zifeng Wu, Chunhua Shen, and Anton Van Den Hengel · 2019
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Cutmix: Regularization strategy to train strong classifiers with localizable features
Sangdoo Yun, Dongyoon Han, Seong Joon Oh, Sanghyuk Chun, Junsuk Choe, and Youngjoon Yoo · 2019
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Joint learning of saliency detection and weakly supervised semantic segmentation
Yu Zeng, Yunzhi Zhuge, Huchuan Lu, and Lihe Zhang · 2019
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Vostr: Video object segmentation via transferable representations
Yi-Wen Chen, Yi-Hsuan Tsai, Yen-Yu Lin, and Ming-Hsuan Yang · 2020
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Momentum contrast for unsupervised visual representation learning
Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross Girshick · 2020
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