Closed-Form Factorization of Latent Semantics in GANs
暂无分享,去创建一个
[1] Li Fei-Fei,et al. ImageNet: A large-scale hierarchical image database , 2009, CVPR.
[2] Serge J. Belongie,et al. Arbitrary Style Transfer in Real-Time with Adaptive Instance Normalization , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[3] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[4] Yinda Zhang,et al. LSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans in the Loop , 2015, ArXiv.
[5] Bolei Zhou,et al. Semantic Hierarchy Emerges in Deep Generative Representations for Scene Synthesis , 2019, ArXiv.
[6] C'eline Hudelot,et al. Controlling generative models with continuous factors of variations , 2020, ICLR.
[7] Sepp Hochreiter,et al. GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium , 2017, NIPS.
[8] Phillip Isola,et al. On the "steerability" of generative adversarial networks , 2019, ICLR.
[9] Deli Zhao,et al. In-Domain GAN Inversion for Real Image Editing , 2020, ECCV.
[10] Bolei Zhou,et al. GAN Dissection: Visualizing and Understanding Generative Adversarial Networks , 2018, ICLR.
[11] Artem Babenko,et al. Unsupervised Discovery of Interpretable Directions in the GAN Latent Space , 2020, ICML.
[12] Timo Aila,et al. A Style-Based Generator Architecture for Generative Adversarial Networks , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[13] Aude Oliva,et al. GANalyze: Toward Visual Definitions of Cognitive Image Properties , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[14] Xiaogang Wang,et al. Deep Learning Face Attributes in the Wild , 2014, 2015 IEEE International Conference on Computer Vision (ICCV).
[15] Léon Bottou,et al. Wasserstein Generative Adversarial Networks , 2017, ICML.
[16] Bolei Zhou,et al. Interpreting the Latent Space of GANs for Semantic Face Editing , 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[17] Yoshua Bengio,et al. Generative Adversarial Nets , 2014, NIPS.
[18] Bolei Zhou,et al. Image Processing Using Multi-Code GAN Prior , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[19] Jaakko Lehtinen,et al. Progressive Growing of GANs for Improved Quality, Stability, and Variation , 2017, ICLR.
[20] Soumith Chintala,et al. Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks , 2015, ICLR.
[21] Pieter Abbeel,et al. InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets , 2016, NIPS.
[22] Jeff Donahue,et al. Large Scale GAN Training for High Fidelity Natural Image Synthesis , 2018, ICLR.
[23] Jaakko Lehtinen,et al. GANSpace: Discovering Interpretable GAN Controls , 2020, NeurIPS.
[24] Ramesh Raskar,et al. Streetscore -- Predicting the Perceived Safety of One Million Streetscapes , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops.
[25] Jaakko Lehtinen,et al. Analyzing and Improving the Image Quality of StyleGAN , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[26] Christopher Burgess,et al. beta-VAE: Learning Basic Visual Concepts with a Constrained Variational Framework , 2016, ICLR 2016.
[27] Bolei Zhou,et al. InterFaceGAN: Interpreting the Disentangled Face Representation Learned by GANs , 2020, IEEE transactions on pattern analysis and machine intelligence.
[28] Yingtao Tian,et al. Towards the High-quality Anime Characters Generation with Generative Adversarial Networks , 2017 .