X-Image-Processing

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X-Image-Processing

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X-Image-Processing is dedicated to presenting the research efforts of XPixel in the realm of image restoration and enhancement.

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 XPixel Homepage
 
 <a href="http://xpixel.group/">
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# Introduction

**X-Image-Processing** is dedicated to presenting the research efforts of XPixel in the realm of image restoration and enhancement.

- **Restoration** techniques are designed to rectify degraded or damaged images, revitalizing their visual quality.
- **Enhancement** strategies focus on refining image attributes such as sharpness, contrast, and color balance.

Since our group highly focuses on super-resolution (SR), we place all the works **related to SR** in [X-Super Resolution](https://github.com/Open-XSource/X-Super-Resolution).

# Table of Contents

- [Image Restoration](#image-restoration)
- [Image Enhancement](#image-enhancement)

# Papers

## Image Restoration

- DegAE: A New Pretraining Paradigm for Low-level Vision 
 Yihao Liu, Jingwen He, Jinjin Gu, Xiangtao Kong, Yu Qiao, Chao Dong 
 Accepted at CVPR'23 (highlight)

- Rethinking Learning-based Demosaicing, Denoising, and Super-Resolution Pipeline 
 Guocheng Qian, Yuanhao Wang, Jinjin Gu, Chao Dong, Wolfgang Heidrich1 , Bernard Ghanem1 , Jimmy S. Ren 
 Accepted at ICCP'22 
 :scroll:[`paper`](https://arxiv.org/abs/1905.02538) :computer:[`code`](https://github.com/guochengqian/TENet)

- UDC-UNet: Under-Display Camera Image Restoration via U-shape Dynamic Network 
 Xina Liu, Jinfan Hu, Xiangyu Chen, Chao Dong 
 Accepted at ECCVW'22 
 :scroll:[`paper`](https://arxiv.org/abs/2209.01809) :computer:[`code`](https://github.com/J-FHu/UDCUNet)

- Fine-grained Face Editing via Personalized Spatial-aware Affine Modulation 
 Si Liu, Renda Bao, Defa Zhu, Shaofei Huang, Qiong Yan, Liang Lin, Chao Dong 
 Accepted at TMM'22 
 :scroll:[`paper`](https://ieeexplore.ieee.org/abstract/document/9769916)

- VQFR: Blind Face Restoration with Vector-Quantized Dictionary and Parallel Decoder 
 GYuchao Gu, Xintao Wang, Liangbin Xie, Chao Dong, Gen Li, Ying Shan, Ming-Ming Cheng 
 Accepted at ECCV'22 
 :scroll:[`paper`](https://arxiv.org/abs/2205.06803) :computer:[`code`](https://github.com/TencentARC/VQFR/)

- Blind Image Restoration Based on Cycle-Consistent Network 
 Shixiang Wu, Chao Dong, Yu Qiao 
 Accepted at TMM'22 
 :scroll:[`paper`](https://ieeexplore.ieee.org/abstract/document/9671019)

- Interactive Multi-Dimension Modulation for Image Restoration 
 Jingwen He, Chao Dong, Liu Yihao, Yu Qiao 
 Accepted at TPAMI'21 
 :scroll:[`paper`](https://arxiv.org/abs/1912.05293) :computer:[`code`](https://github.com/hejingwenhejingwen/AdaFM)

- Path-Restore: Learning Network Path Selection for Image Restoration 
 Ke Yu, Xintao Wang, Chao Dong, Xiaoou Tang, Chen Change Loy 
 Accepted at TPAMI'21 
 :scroll:[`paper`](https://arxiv.org/abs/1904.10343) :computer:[`code`](https://github.com/yuke93/Path-Restore)

- Toward Interactive Modulation for Photo-Realistic Image Restoration 
 Haoming Cai, Jingwen He, Yu Qiao, Chao Dong 
 Accepted at CVPRW'21 
 :scroll:[`paper`](https://arxiv.org/abs/2105.03085)

- Interactive Multi-dimension Modulation with Dynamic Controllable Residual Learning for Image Restoration 
 Jingwen He, Chao Dong, Yu Qiao 
 Accepted at ECCV'20 
 :scroll:[`paper`](https://arxiv.org/abs/1912.05293) :computer:[`code`](https://github.com/hejingwenhejingwen/CResMD)

- Modulating Image Restoration With Continual Levels via Adaptive Feature Modification Layers 
 Jingwen He, Chao Dong, Yu Qiao 
 Accepted at CVPR'19 (oral) 
 :scroll:[`paper`](https://arxiv.org/abs/1904.08118) :computer:[`code`](https://github.com/hejingwenhejingwen/AdaFM)

- Crafting a Toolchain for Image Restoration by Deep Reinforcement Learning 
 Ke Yu, Chao Dong, Liang Lin, Chen Change Loy 
 Accepted at CVPR'18 
 :scroll:[`paper`](https://arxiv.org/abs/1804.03312) :computer:[`code`](https://github.com/yuke93/RL-Restore)

## Image Enhancement

- Very Lightweight Photo Retouching Network with Conditional Sequential Modulation 
 Yihao Liu, Jingwen He, Xiangyu Chen, Zhengwen Zhang, Hengyuan Zhao, Chao Dong, Yu Qiao 
 Accepted at TMM'22 
 :scroll:[`paper`](https://arxiv.org/abs/2104.06279) :computer:[`code`](https://github.com/lyh-18/CSRNet)

- Conditional Sequential Modulation for Efficient Global Image Retouching 
 Jingwen He, Yihao Liu, Yu Qiao, Chao Dong 
 Accepted at ECCV'20 
 :scroll:[`paper`](https://arxiv.org/abs/2009.10390) :computer:[`code`](https://github.com/hejingwenhejingwen/CSRNet)

- HDRUNet: Single Image HDR Reconstruction with Denoising and Dequantization 
 Xiangyu Chen, Yihao Liu, Zhengwen Zhang, Yu Qiao, Chao Dong 
 Accepted at CVPRW'21 
 :scroll:[`paper`](https://arxiv.org/abs/2105.13084) :computer:[`code`](https://github.com/chxy95/HDRUNet)

- A New Journey from SDRTV to HDRTV 
 Xiangyu Chen, Zhengwen Zhang, Jimmy S. Ren, Lynhoo Tian, Yu Qiao, Chao Dong 
 Accepted at ICCV'21 
 :scroll:[`paper`](https://arxiv.org/abs/2108.07978) :computer:[`code`](https://github.com/chxy95/HDRTVNet)

# License

This project is released under the [Apache 2.0 license](LICENSE).

# Projects in Open-XSource

- [X-Super Resolution](https://github.com/XPixelGroup/X-Super-Resolution): Algorithms in the realm of image super-resolution.
- [X-Image Processing](https://github.com/XPixelGroup/X-Image-Processing): Algorithms in the realm of image restoration and enhancement.
- [X-Video Processing](https://github.com/XPixelGroup/X-Video-Processing): Algorithms for processing videos.
- [X-Low level Interpretation](https://github.com/XPixelGroup/X-Low-level-Interpretation): Algorithms for interpreting the principle of neural networks in low-level vision field.
- [X-Evaluation and Benchmark](https://github.com/XPixelGroup/X-Evaluation-and-Benchmark): Datasets for training or evaluating state-of-the-art algorithms.

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