论文解读：Cycle ISP Real Image Restoration via Improved Data Synthesis
Cycle ISP: Real Image Restoration via Improved Data Synthesishtml 谷歌去年发表了一篇文章：Unprocessing Images for Learned Raw Denoising，是关于如何构造逼近真实的数据来进行降噪的，在去年的文章里，研究者们主要是模拟了 ISP 中从 RAW 图到 sRGB 的过程，而后将 ISP 的过程逆转
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相关文章
- 1. 去噪论文“CycleISP: Real Image Restoration via Improved Data Synthesis”
- 2. Generative Adversarial Text to Image Synthesis 论文解读
- 3. 论文阅读笔记之——《Image Restoration via Residual Non-local Attention Networks》
- 4. [论文]记 Improved Image Captioning via Policy Gradient optimization of SPIDEr 论文报告
- 5. 论文阅读——Towards Adversarial Retinal Image Synthesis
- 6. 【论文解读】CVPR：Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
- 7. Real-Time Adaptive Image Compression解读
- 8. Scale-wise Convolution for Image Restoration论文理解
- 9. 《Learning Enriched Features for Real Image Restoration and Enhancement》
- 10. 论文解读之MemNet: A Persistent Memory Network for Image Restoration