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Learning from weakly-supervised data is one of the main challenges in machine learning and computer vision, especially for tasks such as image semantic segmentation where labeling is extremely expensive and subjective.
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Visual attention mediated by biased competition in extrastriate visual cortex
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Object detection with discriminatively trained part-based models
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Deep hierarchies in the primate visual cortex: What can we learn for computer vision?
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Natural scene statistics account for the representation of scene categories in human visual cortex
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Learning collections of part models for object recognition
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Semantic image segmentation with deep convolutional nets and fully connected crfs
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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, Deva Ramanan, and Thomas S. Huang · 2015
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Bottom-up and top-down reasoning with convolutional latent-variable models
Peiyun Hu and Deva Ramanan · 2015
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Fully convolutional networks for semantic segmentation
Jonathan Long, Evan Shelhamer, and Trevor Darrell · 2015
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Segnet: A deep convolutional encoder-decoder architecture for image segmentation
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U-Net: Convolutional Networks for Biomedical Image Segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 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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Going deeper with convolutions
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich · 2015
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Is object localization for free? - weakly-supervised learning with convolutional neural networks
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Shuai Zheng, Sadeep Jayasumana, Bernardino Romera-Paredes, Vibhav Vineet, Zhizhong Su, Dalong Du, Chang Huang, and Philip H. S. Torr · 2015
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Weakly-and semi-supervised learning of a deep convolutional network for semantic image segmentation
George Papandreou, Liang-Chieh Chen, Kevin P. 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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Understanding deep image representations by inverting them
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Weakly supervised object localization with progressive domain adaptation
Dong Li, Jia-Bin Huang, Yali Li, Shengjin Wang, and Ming-Hsuan Yang · 2016
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