Implementation of WResVLM, from the following paper:
Towards Real-World Adverse Weather Image Restoration: Enhancing Clearness and Semantics with Vision-Language Models (ECCV 2024)
Jiaqi Xu, Mengyang Wu, Xiaowei Hu, Chi-Wing Fu, Qi Dou, Pheng-Ann Heng
We use several (pseudo-)synthetic datasets, including Outdoor-Rain, RainDrop, SPA, OTS, Snow100K. Meanwhile, we use real-world data from URHI and our collected real rain and snow images for model training. The real rain and snow images can be downloaded here.
This project is released under the MIT license. Parts of this project use code, data, and models from other sources, which are subject to their respective licenses.