暂无分享,去创建一个
[1] Zhuowen Tu,et al. Aggregated Residual Transformations for Deep Neural Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[2] Alexei A. Efros,et al. Image-to-Image Translation with Conditional Adversarial Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[3] Honghao Gao,et al. A Food Dish Image Generation Framework Based on Progressive Growing GANs , 2019, CollaborateCom.
[4] Simon Osindero,et al. Conditional Generative Adversarial Nets , 2014, ArXiv.
[5] Takeru Miyato,et al. cGANs with Projection Discriminator , 2018, ICLR.
[6] Jeff Donahue,et al. Large Scale GAN Training for High Fidelity Natural Image Synthesis , 2018, ICLR.
[7] Sepp Hochreiter,et al. GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium , 2017, NIPS.
[8] Xiaogang Wang,et al. StackGAN++: Realistic Image Synthesis with Stacked Generative Adversarial Networks , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[9] Jing Zhang,et al. MirrorGAN: Learning Text-To-Image Generation by Redescription , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[10] Bolei Zhou,et al. Closed-Form Factorization of Latent Semantics in GANs , 2020, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[11] Shiguang Shan,et al. AttGAN: Facial Attribute Editing by Only Changing What You Want , 2017, IEEE Transactions on Image Processing.
[12] Jung-Woo Ha,et al. StarGAN: Unified Generative Adversarial Networks for Multi-domain Image-to-Image Translation , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[13] Antonio Torralba,et al. How to Make a Pizza: Learning a Compositional Layer-Based GAN Model , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[14] Jonathon Shlens,et al. Conditional Image Synthesis with Auxiliary Classifier GANs , 2016, ICML.
[15] Harshad Rai,et al. Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks , 2018 .
[16] Tero Karras,et al. Training Generative Adversarial Networks with Limited Data , 2020, NeurIPS.
[17] Jaakko Lehtinen,et al. Progressive Growing of GANs for Improved Quality, Stability, and Variation , 2017, ICLR.
[18] Ori Bar El,et al. GILT: Generating Images from Long Text , 2019, ArXiv.
[19] Gerasimos Spanakis,et al. LoGANv2: Conditional Style-Based Logo Generation with Generative Adversarial Networks , 2019, 2019 18th IEEE International Conference On Machine Learning And Applications (ICMLA).
[20] Zhe Gan,et al. AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[21] Jaakko Lehtinen,et al. Analyzing and Improving the Image Quality of StyleGAN , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[22] Harris Drucker,et al. Improving generalization performance using double backpropagation , 1992, IEEE Trans. Neural Networks.
[23] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[24] Bin Zhu,et al. CookGAN: Causality Based Text-to-Image Synthesis , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[25] Yuichi Yoshida,et al. Spectral Normalization for Generative Adversarial Networks , 2018, ICLR.
[26] Yoshua Bengio,et al. Generative Adversarial Nets , 2014, NIPS.
[27] 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).
[28] Wataru Shimoda,et al. Food image generation using a large amount of food images with conditional GAN: ramenGAN and recipeGAN , 2018, MADiMa@IJCAI.
[29] Vladimir Pavlovic,et al. CookGAN: Meal Image Synthesis from Ingredients , 2020, 2020 IEEE Winter Conference on Applications of Computer Vision (WACV).