Global Perception Feedback Convolutional Neural Networks
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Ran He | Jing Dong | Xiang Wu | Chaoyou Fu | R. He | Chaoyou Fu | Jing Dong | Xiang Wu
[1] R. Desimone. Visual attention mediated by biased competition in extrastriate visual cortex. , 1998, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.
[2] Tieniu Tan,et al. Robust Recovery of Corrupted Low-RankMatrix by Implicit Regularizers , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[3] John K. Tsotsos,et al. Modeling Visual Attention via Selective Tuning , 1995, Artif. Intell..
[4] Ran He,et al. Beyond Face Rotation: Global and Local Perception GAN for Photorealistic and Identity Preserving Frontal View Synthesis , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[5] D C Van Essen,et al. Shifter circuits: a computational strategy for dynamic aspects of visual processing. , 1987, Proceedings of the National Academy of Sciences of the United States of America.
[6] Francis R. Bach,et al. Trace Lasso: a trace norm regularization for correlated designs , 2011, NIPS.
[7] L Chen,et al. Topological structure in visual perception. , 1982, Science.
[8] J. Wolfe,et al. Guided Search 2.0 A revised model of visual search , 1994, Psychonomic bulletin & review.
[9] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[10] S. Kastner,et al. Top-down and bottom-up mechanisms in biasing competition in the human brain , 2009, Vision Research.
[11] Peiyun Hu,et al. Bottom-Up and Top-Down Reasoning with Hierarchical Rectified Gaussians , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[12] Tieniu Tan,et al. Recovery of corrupted low-rank matrices via half-quadratic based nonconvex minimization , 2011, CVPR 2011.
[13] Andrew Zisserman,et al. Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps , 2013, ICLR.
[14] Thomas Brox,et al. Striving for Simplicity: The All Convolutional Net , 2014, ICLR.
[15] Rob Fergus,et al. Visualizing and Understanding Convolutional Networks , 2013, ECCV.
[16] R. Desimone,et al. Neural mechanisms of selective visual attention. , 1995, Annual review of neuroscience.
[17] Dumitru Erhan,et al. Going deeper with convolutions , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[18] Bolei Zhou,et al. Learning Deep Features for Discriminative Localization , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[19] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[20] Andrew Zisserman,et al. Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.
[21] Wei Xu,et al. Look and Think Twice: Capturing Top-Down Visual Attention with Feedback Convolutional Neural Networks , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[22] Xuelong Li,et al. Towards Convolutional Neural Networks Compression via Global Error Reconstruction , 2016, IJCAI.
[23] S Ullman,et al. Shifts in selective visual attention: towards the underlying neural circuitry. , 1985, Human neurobiology.