- Iterative Image Reconstruction
- Super-Resolution (SRCNN) [Web] [Paper-ECCV14] [Paper-arXiv15]
- Learning a Deep Convolutional Network for Image Super-Resolution, ECCV, 2014.
- Image Super-Resolution Using Deep Convolutional Networks, arXiv:1501.00092.
- Very Deep Super-Resolution
- Accurate Image Super-Resolution Using Very Deep Convolutional Networks, arXiv:1511.04587, 2015. [Paper]
- Deeply-Recursive Convolutional Network
- Deeply-Recursive Convolutional Network for Image Super-Resolution, arXiv:1511.04491, 2015. [Paper]
- Casade-Sparse-Coding-Network
- Perceptual Losses for Super-Resolution
- Perceptual Losses for Real-Time Style Transfer and Super-Resolution, arXiv:1603.08155, 2016. [Paper] [Supplementary]
- SRGAN
- Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network, arXiv:1609.04802v3, 2016. [Paper]
- Others
- Image Super-Resolution with Fast Approximate Convolutional Sparse Coding, ICONIP, 2014. [Paper ICONIP-2014]
- Optical Flow (FlowNet) [Paper]
- FlowNet: Learning Optical Flow with Convolutional Networks, arXiv:1504.06852.
- Compression Artifacts Reduction [Paper-arXiv15]
- Compression Artifacts Reduction by a Deep Convolutional Network, arXiv:1504.06993.
- Blur Removal
- Image Deconvolution [Web] [Paper]
- Deep Convolutional Neural Network for Image Deconvolution, NIPS, 2014.
- Deep Edge-Aware Filter [Paper]
- Computing the Stereo Matching Cost with a Convolutional Neural Network [Paper]
- Computing the Stereo Matching Cost with a Convolutional Neural Network, CVPR, 2015.
- Colorful Image Colorization Richard Zhang, Phillip Isola, Alexei A. Efros, ECCV, 2016 [Paper], [Code]
- [Blog]
- Feature Learning by Inpainting[Paper][Code]
- Context Encoders: Feature Learning by Inpainting, CVPR, 2016