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Weakly supervised learning with only coarse labels can obtain visual explanations of deep neural network such as attention maps by back-propagating gradients.
Imagenet: A large-scale hierarchical image database
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei · 2009
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The pascal visual object classes (voc) challenge
M. Everingham, L. Van Gool, C. K. Williams, J. Winn, and A. Zisserman · 2010
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Semantic contours from inverse detectors
B. Hariharan, P. Arbeláez, L. Bourdev, S. Maji, and J. Malik · 2011
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Efficient inference in fully connected crfs with gaussian edge potentials
P. Krähenbühl and V. Koltun · 2011
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Unbiased look at dataset bias
A. Torralba and A. A. Efros · 2011
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Multiscale combinatorial grouping
P. Arbeláez, J. Pont-Tuset, J. T. Barron, F. Marques, and J. Malik · 2014
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Caffe: Convolutional architecture for fast feature embedding
Y. Jia, E. Shelhamer, J. Donahue, S. Karayev, J. Long, R. Girshick, S. Guadarrama, and T. Darrell · 2014
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Network in network
M. Lin, Q. Chen, and S. Yan · 2014
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Deep inside convolutional networks: Visualising image classification models and saliency maps
K. Simonyan, A. Vedaldi, and A. Zisserman · 2014
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Visualizing and understanding convolutional networks
M. D. Zeiler and R. Fergus · 2014
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Object detectors emerge in deep scene cnns
B. Zhou, A. Khosla, A. Lapedriza, A. Oliva, and A. Torralba · 2014
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Look and think twice: Capturing top-down visual attention with feedback convolutional neural networks
C. Cao, X. Liu, Y. Yang, Y. Yu, J. Wang, Z. Wang, Y. Huang, L. Wang, C. Huang, W. Xu, et al · 2015
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Semantic image segmentation with deep convolutional nets and fully connected crfs
L.-C. Chen, G. Papandreou, I. Kokkinos, K. Murphy, and A. L. Yuille · 2015
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Fully convolutional networks for semantic segmentation
J. Long, E. Shelhamer, and T. Darrell · 2015
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Is object localization for free?-weakly-supervised learning with convolutional neural networks
M. Oquab, L. Bottou, I. Laptev, and J. Sivic · 2015
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Weakly-and semi-supervised learning of a dcnn for semantic image segmentation
G. Papandreou, L.-C. Chen, K. Murphy, and A. L. Yuille · 2015
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Constrained convolutional neural networks for weakly supervised segmentation
D. Pathak, P. Krahenbuhl, and T. Darrell · 2015
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From image-level to pixel-level labeling with convolutional networks
P. O. Pinheiro and R. Collobert · 2015
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Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2015
Distinct class-specific saliency maps for weakly supervised semantic segmentation
W. Shimoda and K. Yanai · 2016
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Top-down neural attention by excitation backprop
J. Zhang, Z. Lin, J. Brandt, X. Shen, and S. Sclaroff · 2016
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Learning deep features for discriminative localization
B. Zhou, A. Khosla, A. Lapedriza, A. Oliva, and A. Torralba · 2016
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Learning compositional visual concepts with mutual consistency
Y. Gong, S. Karanam, Z. Wu, K.-C. Peng, J. Ernst, and P. C. Doerschuk · 2017
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Two-phase learning for weakly supervised object localization
D. Kim, D. Cho, D. Yoo, and I. So Kweon · 2017
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Combining bottom-up, top-down, and smoothness cues for weakly supervised image segmentation
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Striving for simplicity: The all convolutional net
J. Springenberg, A. Dosovitskiy, T. Brox, and M. Riedmiller · 2015
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Learning transferrable knowledge for semantic segmentation with deep convolutional neural network
S. Hong, J. Oh, H. Lee, and B. Han · 2016
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Seed, expand and constrain: Three principles for weakly-supervised image segmentation
A. Kolesnikov and C. H. Lampert · 2016
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Dhsnet: Deep hierarchical saliency network for salient object detection
N. Liu and J. Han · 2016
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Augmented feedback in semantic segmentation under image level supervision
X. Qi, Z. Liu, J. Shi, H. Zhao, and J. Jia · 2016
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Built-in foreground/background prior for weakly-supervised semantic segmentation
F. Saleh, M. S. A. Akbarian, M. Salzmann, L. Petersson, S. Gould, and J. M. Alvarez · 2016
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A. Roy and S. Todorovic · 2017
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Grad-cam: Visual explanations from deep networks via gradient-based localization
R. R. Selvaraju, M. Cogswell, A. Das, R. Vedantam, D. Parikh, and D. Batra · 2017
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Hide-and-seek: Forcing a network to be meticulous for weakly-supervised object and action localization
K. K. Singh and Y. J. Lee · 2017
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Object region mining with adversarial erasing: A simple classification to semantic segmentation approach
Y. Wei, J. Feng, X. Liang, M.-M. Cheng, Y. Zhao, and S. Yan · 2017
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Stc: A simple to complex framework for weakly-supervised semantic segmentation
Y. Wei, X. Liang, Y. Chen, X. Shen, M.-M. Cheng, J. Feng, Y. Zhao, and S. Yan · 2017
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Image de-raining using a conditional generative adversarial network
H. Zhang, V. Sindagi, and V. M. Patel · 2017
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Mdnet: A semantically and visually interpretable medical image diagnosis network
Z. Zhang, Y. Xie, F. Xing, M. McGough, and L. Yang · 2017
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