AIGC生成论文汇总

1.1 无特定身份人物生成（Non-identity Generation）

(1) 变分自动编码器（Variational Auto-Encoder）

• 2022, CVPR,Shunyu Yao, RuiZhe Zhong, Yichao Yan, Guangtao Zhai, Xiaokang Yang,DFA-NeRF: Personalized Talking Head Generation via Disentangled Face Attributes Neural Rendering(DFA-NeRF：通过分离的人脸属性神经渲染生成个性化的说话头)
• 2021, CVPR,Daniel, Tal, and Aviv Tamar,Soft-IntroVAE: Analyzing and Improving the Introspective Variational Autoencoder(Soft-IntroVAE：分析和改进自省的变异性 自动编码器)
• 2020, Pattern Recognition,Na Liu, Tao Zhou, Yunfeng Ji, Ziyi Zhao, Lihong Wan,Synthesizing talking faces from text and audio: an autoencoder and sequence-to-sequence convolutional neural network(从文本和音频合成说话的面孔：自动编码器和序列到序列的卷积神经网络)

(2) 生成对抗网络（Generative Adversarial Network）

• 2022, CVPR, Sparse to Dense Dynamic 3D Facial Expression Generation（稀疏到密集的动态 3D 面部表情生成）
• 2022, CVPR, TransEditor: Transformer-Based Dual-Space GAN for Highly Controllable Facial Editing(TransEditor: 基于变换器的双空间GAN用于高度可控的面部编辑)
• 2021, CVPR, Jinsong Zhang, Kun Li, Yu-Kun Lai, Jingyu Yang, PISE: Person Image Synthesis and Editing with Decoupled GAN(PISE：使用解耦 GAN 进行人物图像合成和编辑)
• 2021, CVPR, Fast-GANFIT: Generative Adversarial Network for High Fidelity 3D Face Reconstruction（Fast-GANFIT：用于高保真 3D 人脸重建的生成对抗网络）
• 2020,IEEE Access,Y. Fan, Y. Liu, G. Lv, S. Liu, G. Li and Y. Huang, “Full Face-and-Head 3D Model With Photorealistic Texture,”(具有逼真纹理的全脸和头部 3D 模型)
• 2019, CVPR, GANFIT: Generative Adversarial Network Fitting for High Fidelity 3D Face Reconstruction(GANFIT：用于高保真 3D 人脸重建的生成对抗网络拟合)

1.2 身份转换（Identity Swap）

(1) 不可知论者Subject-Agnostic

• 2022, CVPR,Qi Li, Weining Wang, Chengzhong Xu, Zhenan Sun,FaceSwapper: Learning Disentangled Representation for One-shot Progressive Face Swapping(FaceSwapper：学习用于一次性渐进式人脸交换的分离表示)
• 2022, CVPR,Yangyang Xu, Bailin Deng, Junle Wang, Yanqing Jing, Jia Pan, Shengfeng He,High-resolution Face Swapping via Latent Semantics Disentanglement(通过潜在语义解缠结实现高分辨率人脸交换)
• 2022, CVPR,Chao Xu, Jiangning Zhang, Miao