Unsupervised image-to-image translation using intra-domain reconstruction loss
Tóm tắt
Từ khóa
Tài liệu tham khảo
Dong C, Loy CC, He KM, Tang XO (2016) Image super-resolution using deep convolutional networks. IEEE Trans Pattern Anal Mach Intell 38(2):295–307
Wang XT, Yu K, Wu SX, Gu JJ, Liu YH, Dong, Loy CC, Qiao Y, Tang XO (2018) Enhanced super-resolution generative adversarial networks. In: European conference on computer vision
W.L. Zhang, Y.H. Liu, C. Dong, and Y. Qiao, RankSRGAN: Generative Adversarial Networks With Ranker for Image Super-Resolution, IEEE International Conference on Computer Vision (2019)
Karras T, Laine S, Aila T (2019) A style-based generator architecture for generative adversarial networks. In: IEEE conference on computer vision and pattern recognition
Chang HW, Lu JW, Yu F, Finkelstein A (2018) PairedCycleGAN: asymmetric style transfer for applying and removing makeup. In: IEEE conference on computer vision and pattern recognition
He ZL, Zuo WM, Kan M, Shan SG, Chen XL (2019) AttGAN: facial attribute editing by only changing what you want. IEEE Trans Image Process 28(11):5464–5478
Xiao TH, Hong JP, Ma JW (2018) ELEGANT: exchanging latent encodings with GAN for transferring multiple face attributes. In: European conference on computer vision
Zeng YH, Fu JL, Chao HY, Guo B (2019) Learning pyramid-context encoder network for high-quality image inpainting. In: IEEE conference on computer vision and pattern RecPIognition
Yu JH, Lin Z, Yang JM, Shen XH, Lu X, Huang TS (2018) Generative image inpainting with contextual attention. In: IEEE conference on computer vision and pattern recognition
Goodfellow IJ, Pouget-Abadie J, Mirza M, Xu B, Warde-Farley D, Ozair S, Courville A, Bengio Y (2014) Generative adversarial nets. In: Conference on neural information processing systems, pp 2672–2680
Isola P, Zhu JY, Zhou T, Efros AA (2017) Image-to-image translation with conditional adversarial networks. In: IEEE conference on computer vision and pattern recognition, pp 5967–5976
Wang TC, Liu MY, Zhu JY, Tao A, Kautz J, Catanzaro B (2018) High-resolution image synthesis and semantic manipulation with conditional GANs. In: IEEE conference on computer vision and pattern recognition, pp 8798–8807
Mao Q, Lee HY, Tseng HY, Ma SW, Yang MH (2019) Mode seeking generative adversarial networks for diverse image synthesis. In: IEEE conference on computer vision and pattern recognition
Wang TC, Liu MY, Zhu JY, Liu G, Tao A, Kautz J, Catanzaro B (2018) Video-to-video synthesis. In: Conference on neural information processing systems, pp 1–14
Wang XZ, Xing HJ, Li Y (2015) A study on relationship between generalization abilities and fuzziness of base classifiers in ensemble learning. IEEE Trans Fuzzy Syst 23(5):1638–1654
Wang XZ, Wang R, Xu C (2018) discovering the relationship between generalization and uncertainty by incorporating complexity of classification. IEEE Trans Cybern 48(2):703–715
Zhu JY, Park T, Isola P, Efros AA (2017) Unpaired image-to-image translation using cycle-consistent adversarial networks. In: IEEE international conference on computer vision, pp 2242–2251
Yi Z, Zhang H, Tan P, Gong M (2017) DualGAN: unsupervised dual learning for image-to-image translation. In: IEEE international conference on computer vision, pp 2868–2876
Kim T, Cha M, Kim H, Lee JK, Kim J (2017) Learning to discover cross domain relations with generative adversarial networks. In: International conference on machine learning
Chen Y, Lai YK, Liu YJ (2018) CartoonGAN: generative adversarial networks for photo cartoonization. In: IEEE conference on computer vision and pattern recognition, pp 9465–9474
Lu GS, Zhou ZM, Song YX, Ren K, Yu Y (2019) Guiding the one-to-one mapping in CycleGAN via optimal transport. In: The thirty-third AAAI conference on artificial intelligence
Liu MY, Breuel T, Kautz J (2017) Unsupervised image-to-image translation networks. In: NeurIPS, pp 700–708
Huang X, Liu MY, Belongie S, Kautz J (2018) Multi-modal unsupervised image-to-image translation. In: European conference on computer vision
Lee HY, Tseng HY, Huang JB, Singh M, Yang MH (2018) Diverse image-to-image translation via disentangled representations. In: European conference on computer vision, pp 35–51
Lin J, Xia Y, Qin T, Chen Z, Liu TY (2018) Conditional image-to-image translation. In: IEEE conference on computer vision and pattern recognition
Denton E, Chintala S, Fergus R, Szlam A (2015) Deep generative image models using a Laplacian pyramid of adversarial networks. arXiv:1506.05751
Radford A, Metz L, Chintala S (2016) Unsupervised representation learning with deep convolutional generative adversarial networks. In: International conference of learning representation, pp 1–16
Zhu JY, Krähenbühl P, Shechtman E, Efros AA (2016) Generative visual manipulation on the natural image manifold. In: European conference on computer vision, pp 597–613
Salimans T, Goodfellow I, Zaremba W, Cheung V, Radford A, Chen X (2016) Improved techniques for training GANs. arXiv:1606.03498
Mathieu MF, Zhao J, Ramesh A, Sprechmann P, LeCun Y (2016) Disentangling factors of variation in deep representation using adversarial training. In: Conference on neural information processing systems
Reed S, Akata Z, Yan X, Logeswaran L, Schiele B, Lee H (2016) Generative adversarial text to image synthesis. In: International conference on machine learning
Pathak D, Krahenbuhl P, Donahue J, Darrell T, Efros AA (2016) Context encoders: feature learning by inpainting. In: IEEE conference on computer vision and pattern recognition, pp 2536–2544
Mathieu M, Couprie C, LeCun Y (2015) Deep multiscale video prediction beyond mean square error, pp 1–14. arXiv:1511.05440
Mirza M, Osindero S (2014) Conditional generative adversarial nets. arXiv:1411.1784
Odena A (2016) Semi-supervised learning with generative adversarial networks, pp 1–3. arXiv:1606.01583
Chen X, Duan Y, Houthooft R, Schulman J, Sutskever I, Abbeel P (2016) InfoGAN: interpretable representation learning by information maximizing generative adversarial nets. arXiv:1606.03657
Zhao J, Mathieu M, Lecun Y (2016) Energy-based generative adversarial network, pp 1–17. arXiv:1609.03126
Berthelot D, Schumm T, Metz L (2017) Began: boundary equilibrium generative adversarial networks, pp 1–9. arXiv:1703.10717
Wardefarley D, Bengio Y (2017) Improving generative adversarial networks with denoising feature matching. In: Proceedings of the international conference on learning representations
Larsen ABL, Snderby SK, Larochelle H, Winther O (2016) Autoencoding beyond pixels using a learned similarity metric. arXiv:1512.09300v2
Che T, Li Y, Jacob AP, Bengio Y, Li W (2017) Mode regularized generative adversarial networks. In: International conference on learning representations
Rosca M, Lakshminarayanan B, Warde-Farley D, Mohamed S (2017) Variational approaches for auto-encoding generative adversarial networks. arXiv:1706.04987
Mao X, Li Q, Xie H, Lau RYK, Wang Z, Smolley SP (2017) Least squares generative adversarial networks. In: IEEE conference on computer vision and pattern recognition, pp 2813–2821
Mroueh Y, Sercu T, Goel V (2017) Mcgan: mean and covariance feature matching GAN. In: International conference on machine learning
Arjovsky M, Chintala S, Bottou L (2017) Wasserstein GAN. arXiv:1701.07875
Gulrajani I, Ahmed F, Arjovsky M, Dumoulin V, Courville A (2017) Improved training of Wasserstein GANs. In: Neural information processing systems
Ulyanov D, Vedaldi A, Lempitsky V (2014) Adversarial generator-encoder networks. arXiv:1704.02304
Kodali N, Abernethy J, Hays J, Kira Z (2017) On convergence and stability of GANs. arXiv:1705.07215
Wang XZ, Zhang TL, Wang R (2019) Non-iterative deep learning: incorporating restricted boltzmann machine into multilayer random weight neural networks. IEEE Trans Syst Man Cybern Syst 49(7):1299–1380
Wei W, Wang JH, Liang JY (2015) Compacted decision tables based attribute reduction. Knowl-Based Syst 86:261–277
Wang JH, Liang JY, Qian YH (2010) A heuristic method to attribute reduction for concept lattice. In: 2010 international conference on machine learning and cybernetics, pp 483–487
Wang JH, Qian YH, Liang JY (2009) A new measure of uncertainty based on knowledge granulation for rough sets. Inf Sci 179(4):458–470
Wang R, Wang XZ, Kwong S, Xu C (2017) Incorporating diversity and informativeness in multiple-instance active learning. IEEE Trans Fuzzy Syst 25(6):1460–1475
Mejjati YA, Richardt C, Tompkin J, Cosker D (2018) Unsupervised attention-guided image-to-image translation. In: Conference on neural information processing systems, pp 1–18