Self-supervised GAN for Image Generation by Correlating Image Channels
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Rui Li | Hau-San Wong | Si Wu | Sheng Qian | Wen-ming Cao | H. Wong | Si Wu | Wenming Cao | Sheng Qian | Rui Li
[1] Yann LeCun,et al. Energy-based Generative Adversarial Network , 2016, ICLR.
[2] Rob Fergus,et al. Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks , 2015, NIPS.
[3] Abhinav Gupta,et al. Unsupervised Learning of Visual Representations Using Videos , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[4] Ming-Yu Liu,et al. Coupled Generative Adversarial Networks , 2016, NIPS.
[5] Dimitris N. Metaxas,et al. StackGAN: Text to Photo-Realistic Image Synthesis with Stacked Generative Adversarial Networks , 2016, 2017 IEEE International Conference on Computer Vision (ICCV).
[6] David A. Forsyth,et al. Learning Large-Scale Automatic Image Colorization , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[7] Soumith Chintala,et al. Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks , 2015, ICLR.
[8] Alexei A. Efros,et al. Split-Brain Autoencoders: Unsupervised Learning by Cross-Channel Prediction , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[9] Alexei A. Efros,et al. Unsupervised Visual Representation Learning by Context Prediction , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[10] Raymond Y. K. Lau,et al. Least Squares Generative Adversarial Networks , 2016, 2017 IEEE International Conference on Computer Vision (ICCV).
[11] Thomas Brox,et al. Discriminative Unsupervised Feature Learning with Exemplar Convolutional Neural Networks , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[12] Bin Sheng,et al. Deep Colorization , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[13] Alexei A. Efros,et al. Colorful Image Colorization , 2016, ECCV.
[14] Jitendra Malik,et al. Learning to See by Moving , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[15] Dhruv Batra,et al. LR-GAN: Layered Recursive Generative Adversarial Networks for Image Generation , 2016, ICLR.
[16] Paolo Favaro,et al. Unsupervised Learning of Visual Representations by Solving Jigsaw Puzzles , 2016, ECCV.
[17] Alexei A. Efros,et al. Context Encoders: Feature Learning by Inpainting , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[18] Gregory Shakhnarovich,et al. Colorization as a Proxy Task for Visual Understanding , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[19] Gregory Shakhnarovich,et al. Learning Representations for Automatic Colorization , 2016, ECCV.
[20] Aaron C. Courville,et al. Improved Training of Wasserstein GANs , 2017, NIPS.
[21] Yong Yu,et al. Unsupervised Diverse Colorization via Generative Adversarial Networks , 2017, ECML/PKDD.
[22] Wojciech Zaremba,et al. Improved Techniques for Training GANs , 2016, NIPS.
[23] Yuichi Yoshida,et al. Spectral Normalization for Generative Adversarial Networks , 2018, ICLR.
[24] Abhinav Gupta,et al. Generative Image Modeling Using Style and Structure Adversarial Networks , 2016, ECCV.
[25] Yoshua Bengio,et al. Generative Adversarial Nets , 2014, NIPS.
[26] Zhen Wang,et al. Multi-class Generative Adversarial Networks with the L2 Loss Function , 2016, ArXiv.
[27] Hyunsoo Kim,et al. Learning to Discover Cross-Domain Relations with Generative Adversarial Networks , 2017, ICML.
[28] Sebastian Nowozin,et al. f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization , 2016, NIPS.