Image to Image Translation for Domain Adaptation
暂无分享,去创建一个
David J. Kriegman | Kyungnam Kim | Soheil Kolouri | Ravi Ramamoorthi | Zak Murez | D. Kriegman | R. Ramamoorthi | S. Kolouri | Kyungnam Kim | Zak Murez | Soheil Kolouri
[1] 拓海 杉山,et al. “Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks”の学習報告 , 2017 .
[2] Trevor Darrell,et al. Deep Domain Confusion: Maximizing for Domain Invariance , 2014, CVPR 2014.
[3] Alexei A. Efros,et al. Image-to-Image Translation with Conditional Adversarial Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[4] Ming-Yu Liu,et al. Coupled Generative Adversarial Networks , 2016, NIPS.
[5] Michael I. Jordan,et al. Unsupervised Domain Adaptation with Residual Transfer Networks , 2016, NIPS.
[6] Tomas Pfister,et al. Learning from Simulated and Unsupervised Images through Adversarial Training , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[7] François Laviolette,et al. Domain-Adversarial Training of Neural Networks , 2015, J. Mach. Learn. Res..
[8] Yoshua Bengio,et al. The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
[9] Vladlen Koltun,et al. Playing for Data: Ground Truth from Computer Games , 2016, ECCV.
[10] Jan Kautz,et al. Unsupervised Image-to-Image Translation Networks , 2017, NIPS.
[11] Trevor Darrell,et al. Adapting Visual Category Models to New Domains , 2010, ECCV.
[12] Karsten M. Borgwardt,et al. Covariate Shift by Kernel Mean Matching , 2009, NIPS 2009.
[13] Trevor Darrell,et al. Simultaneous Deep Transfer Across Domains and Tasks , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[14] Inbar Mosseri,et al. XGAN: Unsupervised Image-to-Image Translation for many-to-many Mappings , 2017, Domain Adaptation for Visual Understanding.
[15] Taesung Park,et al. CyCADA: Cycle-Consistent Adversarial Domain Adaptation , 2017, ICML.
[16] Sebastian Ramos,et al. The Cityscapes Dataset for Semantic Urban Scene Understanding , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[17] Trevor Darrell,et al. FCNs in the Wild: Pixel-level Adversarial and Constraint-based Adaptation , 2016, ArXiv.
[18] Thomas A. Funkhouser,et al. Dilated Residual Networks , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[19] Raymond Y. K. Lau,et al. Least Squares Generative Adversarial Networks , 2016, 2017 IEEE International Conference on Computer Vision (ICCV).
[20] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[21] Victor S. Lempitsky,et al. Unsupervised Domain Adaptation by Backpropagation , 2014, ICML.
[22] Jonathan J. Hull,et al. A Database for Handwritten Text Recognition Research , 1994, IEEE Trans. Pattern Anal. Mach. Intell..
[23] Dumitru Erhan,et al. Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[24] Antonio M. López,et al. The SYNTHIA Dataset: A Large Collection of Synthetic Images for Semantic Segmentation of Urban Scenes , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[25] Silvio Savarese,et al. Learning Transferrable Representations for Unsupervised Domain Adaptation , 2016, NIPS.
[26] Andrew Y. Ng,et al. Reading Digits in Natural Images with Unsupervised Feature Learning , 2011 .
[27] Carlos D. Castillo,et al. Generate to Adapt: Aligning Domains Using Generative Adversarial Networks , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[28] Qilong Wang,et al. Mind the Class Weight Bias: Weighted Maximum Mean Discrepancy for Unsupervised Domain Adaptation , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[29] Qiao Wang,et al. VirtualWorlds as Proxy for Multi-object Tracking Analysis , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[30] Kilian Q. Weinberger,et al. Densely Connected Convolutional Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[31] Sethuraman Panchanathan,et al. Deep Hashing Network for Unsupervised Domain Adaptation , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[32] Yoshua Bengio,et al. Generative Adversarial Nets , 2014, NIPS.
[33] Zhen Wang,et al. Multi-class Generative Adversarial Networks with the L2 Loss Function , 2016, ArXiv.
[34] Trevor Darrell,et al. Adversarial Discriminative Domain Adaptation , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[35] Lior Wolf,et al. Unsupervised Cross-Domain Image Generation , 2016, ICLR.
[36] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[37] Aaron C. Courville,et al. Improved Training of Wasserstein GANs , 2017, NIPS.
[38] Yoshua Bengio,et al. Gradient-based learning applied to document recognition , 1998, Proc. IEEE.
[39] Michael I. Jordan,et al. Learning Transferable Features with Deep Adaptation Networks , 2015, ICML.
[40] Mengjie Zhang,et al. Deep Reconstruction-Classification Networks for Unsupervised Domain Adaptation , 2016, ECCV.
[41] Fei-Fei Li,et al. Label Efficient Learning of Transferable Representations acrosss Domains and Tasks , 2017, NIPS.