Cross-Modal Contrastive Learning for Text-to-Image Generation
暂无分享,去创建一个
[1] Aaron C. Courville,et al. Generative Adversarial Networks , 2022, 2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT).
[2] Honglak Lee,et al. Text-to-Image Generation Grounded by Fine-Grained User Attention , 2020, 2021 IEEE Winter Conference on Applications of Computer Vision (WACV).
[3] Alexei A. Efros,et al. Contrastive Learning for Unpaired Image-to-Image Translation , 2020, ECCV.
[4] Ngai-Man Cheung,et al. InfoMax-GAN: Improved Adversarial Image Generation via Information Maximization and Contrastive Learning , 2020, 2021 IEEE Winter Conference on Applications of Computer Vision (WACV).
[5] Jaesik Park,et al. ContraGAN: Contrastive Learning for Conditional Image Generation , 2020, NeurIPS.
[6] Sameer Singh,et al. Image Augmentations for GAN Training , 2020, ArXiv.
[7] Chen Sun,et al. What makes for good views for contrastive learning , 2020, NeurIPS.
[8] Jason Baldridge,et al. Crisscrossed Captions: Extended Intramodal and Intermodal Semantic Similarity Judgments for MS-COCO , 2020, EACL.
[9] N. Vasconcelos,et al. Audio-Visual Instance Discrimination with Cross-Modal Agreement , 2020, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[10] Jiaolong Yang,et al. Disentangled and Controllable Face Image Generation via 3D Imitative-Contrastive Learning , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[11] Kaiming He,et al. Improved Baselines with Momentum Contrastive Learning , 2020, ArXiv.
[12] Geoffrey E. Hinton,et al. A Simple Framework for Contrastive Learning of Visual Representations , 2020, ICML.
[13] Wenjie Pei,et al. CPGAN: Full-Spectrum Content-Parsing Generative Adversarial Networks for Text-to-Image Synthesis , 2019, ArXiv.
[14] Jordi Pont-Tuset,et al. Connecting Vision and Language with Localized Narratives , 2019, ECCV.
[15] Ross B. Girshick,et al. Momentum Contrast for Unsupervised Visual Representation Learning , 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[16] Stefan Wermter,et al. Semantic Object Accuracy for Generative Text-to-Image Synthesis , 2019, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[17] Honglak Lee,et al. Consistency Regularization for Generative Adversarial Networks , 2019, ICLR.
[18] S. Ermon,et al. Understanding the Limitations of Variational Mutual Information Estimators , 2019, ICLR.
[19] Xin Li,et al. Semantics-Enhanced Adversarial Nets for Text-to-Image Synthesis , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[20] Philip H. S. Torr,et al. Controllable Text-to-Image Generation , 2019, NeurIPS.
[21] Thomas Fevens,et al. Dual Adversarial Inference for Text-to-Image Synthesis , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[22] Nenghai Yu,et al. Semantics Disentangling for Text-To-Image Generation , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[23] Wei Chen,et al. DM-GAN: Dynamic Memory Generative Adversarial Networks for Text-To-Image Synthesis , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[24] Jing Zhang,et al. MirrorGAN: Learning Text-To-Image Generation by Redescription , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[25] Lei Zhang,et al. Object-Driven Text-To-Image Synthesis via Adversarial Training , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[26] K. Chandrasekran,et al. Geometric , 2019, Encyclopedic Dictionary of Archaeology.
[27] S. Wermter,et al. Generating Multiple Objects at Spatially Distinct Locations , 2019, ICLR.
[28] Jeff Donahue,et al. Large Scale GAN Training for High Fidelity Natural Image Synthesis , 2018, ICLR.
[29] Ting Chen,et al. On Self Modulation for Generative Adversarial Networks , 2018, ICLR.
[30] Joon Son Chung,et al. Perfect Match: Improved Cross-modal Embeddings for Audio-visual Synchronisation , 2018, ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[31] Oriol Vinyals,et al. Representation Learning with Contrastive Predictive Coding , 2018, ArXiv.
[32] Radu Soricut,et al. Conceptual Captions: A Cleaned, Hypernymed, Image Alt-text Dataset For Automatic Image Captioning , 2018, ACL.
[33] Stella X. Yu,et al. Unsupervised Feature Learning via Non-parametric Instance Discrimination , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[34] Han Zhang,et al. Self-Attention Generative Adversarial Networks , 2018, ICML.
[35] Lin Yang,et al. Photographic Text-to-Image Synthesis with a Hierarchically-Nested Adversarial Network , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[36] Yuichi Yoshida,et al. Spectral Normalization for Generative Adversarial Networks , 2018, ICLR.
[37] Han Zhang,et al. Improving GANs Using Optimal Transport , 2018, ICLR.
[38] Hui Chen,et al. Geometry-Contrastive GAN for Facial Expression Transfer. , 2018, 1802.01822.
[39] Seunghoon Hong,et al. Inferring Semantic Layout for Hierarchical Text-to-Image Synthesis , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[40] Aaron C. Courville,et al. Mutual Information Neural Estimation , 2018, ICML.
[41] Rishi Sharma,et al. A Note on the Inception Score , 2018, ArXiv.
[42] 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.
[43] Léon Bottou,et al. Wasserstein Generative Adversarial Networks , 2017, ICML.
[44] Sepp Hochreiter,et al. GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium , 2017, NIPS.
[45] Sergio Gomez Colmenarejo,et al. Parallel Multiscale Autoregressive Density Estimation , 2017, ICML.
[46] Dustin Tran,et al. Hierarchical Implicit Models and Likelihood-Free Variational Inference , 2017, NIPS.
[47] Yoshua Bengio,et al. Plug & Play Generative Networks: Conditional Iterative Generation of Images in Latent Space , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[48] Raymond Y. K. Lau,et al. Least Squares Generative Adversarial Networks , 2016, 2017 IEEE International Conference on Computer Vision (ICCV).
[49] Alex Graves,et al. Conditional Image Generation with PixelCNN Decoders , 2016, NIPS.
[50] Wojciech Zaremba,et al. Improved Techniques for Training GANs , 2016, NIPS.
[51] Bernt Schiele,et al. Generative Adversarial Text to Image Synthesis , 2016, ICML.
[52] Li Fei-Fei,et al. Perceptual Losses for Real-Time Style Transfer and Super-Resolution , 2016, ECCV.
[53] Sergey Ioffe,et al. Rethinking the Inception Architecture for Computer Vision , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[54] Alex Graves,et al. DRAW: A Recurrent Neural Network For Image Generation , 2015, ICML.
[55] Andrew Zisserman,et al. Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.
[56] Pietro Perona,et al. Microsoft COCO: Common Objects in Context , 2014, ECCV.
[57] Max Welling,et al. Auto-Encoding Variational Bayes , 2013, ICLR.
[58] Pietro Perona,et al. The Caltech-UCSD Birds-200-2011 Dataset , 2011 .
[59] Andrew Zisserman,et al. Automated Flower Classification over a Large Number of Classes , 2008, 2008 Sixth Indian Conference on Computer Vision, Graphics & Image Processing.
[60] Liam Paninski,et al. Estimation of Entropy and Mutual Information , 2003, Neural Computation.
[61] Ming-Wei Chang,et al. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding , 2019, NAACL.
[62] Dacheng Tao,et al. Learn, Imagine and Create: Text-to-Image Generation from Prior Knowledge , 2019, NeurIPS.
[63] Jon Gauthier. Conditional generative adversarial nets for convolutional face generation , 2015 .