論文解讀：Cycle ISP Real Image Restoration via Improved Data Synthesis
Cycle ISP: Real Image Restoration via Improved Data Synthesishtml 谷歌去年發表了一篇文章：Unprocessing Images for Learned Raw Denoising，是關於如何構造逼近真實的數據來進行降噪的，在去年的文章裏，研究者們主要是模擬了 ISP 中從 RAW 圖到 sRGB 的過程，而後將 ISP 的過程逆轉
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相關文章
- 1. 去噪論文「CycleISP: Real Image Restoration via Improved Data Synthesis」
- 2. Generative Adversarial Text to Image Synthesis 論文解讀
- 3. 論文閱讀筆記之——《Image Restoration via Residual Non-local Attention Networks》
- 4. [論文]記 Improved Image Captioning via Policy Gradient optimization of SPIDEr 論文報告
- 5. 論文閱讀——Towards Adversarial Retinal Image Synthesis
- 6. 【論文解讀】CVPR：Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
- 7. Real-Time Adaptive Image Compression解讀
- 8. Scale-wise Convolution for Image Restoration論文理解
- 9. 《Learning Enriched Features for Real Image Restoration and Enhancement》
- 10. 論文解讀之MemNet: A Persistent Memory Network for Image Restoration