总览¶
模型权重文件数量: 70
配置文件数量: 65
论文数量: 25
ALGORITHM: 25
有关支持的数据集，请参阅 数据集总览。
补全模型¶
模型权重文件数量: 8
配置文件数量: 8
论文数量: 4
[ALGORITHM] Free-Form Image Inpainting With Gated Convolution (⇨)
[ALGORITHM] Generative Image Inpainting With Contextual Attention (⇨)
[ALGORITHM] Globally and Locally Consistent Image Completion (⇨)
[ALGORITHM] Image Inpainting for Irregular Holes Using Partial Convolutions (⇨)
抠图模型¶
模型权重文件数量: 9
配置文件数量: 9
论文数量: 3
[ALGORITHM] Deep Image Matting (⇨)
[ALGORITHM] Indices Matter: Learning to Index for Deep Image Matting (⇨)
[ALGORITHM] Natural Image Matting via Guided Contextual Attention (⇨)
超分辨率模型¶
模型权重文件数量: 43
配置文件数量: 38
论文数量: 16
[ALGORITHM] Basicvsr: The Search for Essential Components in Video Super-Resolution and Beyond (⇨ ⇨)
[ALGORITHM] Basicvsr++: Improving Video Super-Resolution With Enhanced Propagation and Alignment (⇨)
[ALGORITHM] Deep Face Super-Resolution With Iterative Collaboration Between Attentive Recovery and Landmark Estimation (⇨)
[ALGORITHM] Edvr: Video Restoration With Enhanced Deformable Convolutional Networks (⇨)
[ALGORITHM] Enhanced Deep Residual Networks for Single Image Super-Resolution (⇨)
[ALGORITHM] Esrgan: Enhanced Super-Resolution Generative Adversarial Networks (⇨)
[ALGORITHM] Glean: Generative Latent Bank for Large-Factor Image Super-Resolution (⇨)
[ALGORITHM] Image Super-Resolution Using Deep Convolutional Networks (⇨)
[ALGORITHM] Learning Continuous Image Representation With Local Implicit Image Function (⇨)
[ALGORITHM] Learning Texture Transformer Network for Image Super-Resolution (⇨)
[ALGORITHM] Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network (⇨)
[ALGORITHM] Real-Esrgan: Training Real-World Blind Super-Resolution With Pure Synthetic Data (⇨)
[ALGORITHM] Realbasicvsr: Investigating Tradeoffs in Real-World Video Super-Resolution (⇨)
[ALGORITHM] Residual Dense Network for Image Super-Resolution (⇨)
[ALGORITHM] Tdan: Temporally-Deformable Alignment Network for Video Super-Resolution (⇨)
[ALGORITHM] Video Enhancement With Task-Oriented Flow (⇨)