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基于深度学习的Image Inpainting(论文+代码)

参考链接:基于深度学习的Image Inpainting (图像修复)

基于深度学习的Image Inpainting

==================已暂停更新=============

毕业论文做的是图像修复方面的研究,目前毕业论文已经基本结束,把之前看过的论文和代码进行分析整理一遍,分别会对论文和代码进行讲解,理解不对的地方还请指出。

这里会将讲解的内容放到随笔中,这里贴出相应的链接,方便查找。

1. Context Encoder 《Context Encoders: Feature Learning by Inpainting》

论文链接:https://arxiv.org/abs/1604.07379
github链接:https://github.com/pathak22/context-encoder   (Torch版本)

https://github.com/BoyuanJiang/context_encoder_pytorch   (Pytorch版本)

论文及代码解读:Context Encoder论文及代码解读

2. High Resolution Inpainting  《High-Resolution Image Inpainting using Multi-Scale Neural Patch Synthesis》

论文链接:https://arxiv.org/abs/1611.09969

github链接:https://github.com/leehomyc/Faster-High-Res-Neural-Inpainting    (Torch版本)

3. on demanding learning  《On-Demand Learning for Deep Image Restoration》

论文链接:http://vision.cs.utexas.edu/projects/on_demand_learning/

github链接:https://github.com/rhgao/on-demand-learning    (Torch版本)

4. SIGGRAPH 2017《Globally and Locally Consistent Image Completion》

论文链接:http://iizuka.cs.tsukuba.ac.jp/projects/completion/en/

github链接:https://github.com/satoshiiizuka/siggraph2017_inpainting   (Torch版本)

https://github.com/shinseung428/GlobalLocalImageCompletion_TF   (Tensorflow1.4)

5. ICLR 2018   《Image Inpainting for Irregular Holes Using Partial Convolutions》

论文链接:https://arxiv.org/abs/1804.07723

github链接:暂无

6. CVPR 2018    《Generative Image Inpainting with Contextual Attention》

论文链接:https://arxiv.org/abs/1801.07892

github链接:https://github.com/JiahuiYu/generative_inpainting    (Tensorflow1.3.0+)

另一片佳作:《Free-Form Image Inpainting with Gated Convolution》

论文链接:https://arxiv.org/abs/1806.03589

github链接:暂无

7.  《Shift-Net: Image Inpainting via Deep Feature Rearrangement》

论文链接:https://arxiv.org/abs/1801.09392

github链接:暂无

8.  《Deep Image Prior》

项目主页:https://dmitryulyanov.github.io/deep_image_prior

论文链接:在主页中paper链接

github链接:https://github.com/DmitryUlyanov/deep-image-prior   (Pytorch版本)

9. ECCV 2018   《Contextual Based Image Inpainting: Infer, Match and Translate》

论文链接:https://arxiv.org/abs/1711.08590v3

github链接:暂无

posted on 2019-04-01 14:28  王老头  阅读(7251)  评论(1编辑  收藏  举报