{"repo":"Fediory/HVI-CIDNet","free":true,"listed":false,"github":"https://github.com/Fediory/HVI-CIDNet","clone":"git clone https://github.com/Fediory/HVI-CIDNet.git","description":"[CVPR2025 && NTIRE2025] HVI: A New Color Space for Low-light Image Enhancement (Official Implementation)","language":"Python","stars":838,"topics":["image-enhancement","image-processing","low-light-image-enhancement","transformer","hvi-color-space","cvpr"],"license":"MIT","category":"media-processing","readme_excerpt":"  [CVPR2025] HVI: A New Color Space for Low-light Image Enhancement Qingsen Yan ∗ , Yixu Feng ∗ , Cheng Zhang , Guansong Pang, Kangbiao Shi, Peng Wu, Wei Dong, Jinqiu Sun, Yanning Zhang Previous Version: You Only Need One Color Space: An Efficient Network for Low-light Image Enhancement   HVI-CIDNet Demo: News 🆕 - 2025.10.27 Thanks shade233 for helping me to fix the conflicts and incorrect usage of argparser. - 2025.07.11 Upgraded version paper as \"HVI-CIDNet+: Beyond Extreme Darkness for Low-Light Image Enhancement\" in Arxiv. The new code, models and results will be uploaded soon. (code link：Github) - 2025.06.03 Special Thanks for Kangbiao Shi for training HVI-CIDNet on FiveK dataset follow retinexformer. The training code and models are avaliable now. 🔆 - 2025.05.01 Our NTIRE2025 LLIE track championship solution, FusionNet, is now public at Arxiv! 📝 - 2025.03.27 Congratulations! Our team achived 1st place in the competition: NTIRE 2025 Low Light Image Enhancement Challenge (If you have any question about our NTIRE method, please contact: Kangbiao Shi, email: 18334840904@163.com). We fused our HVI-CIDNet with last year's winner and runner-up models to get the optimal results. We will explain the fusion method thoroughly in detail in the report for subsequent reference. 🚀 - 2025.03.10 All weights are public at Hugging Face. Special Thanks to Niels Rogge, Wauplin, and hysts.🔆 - 2025.02.26 Congratulations! Our final-version paper \"HVI: A New color space for Low-l","default_branch":null,"files":null,"tree":[],"storefront":"/r/Fediory","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/Fediory/HVI-CIDNet/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}