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Light-VQA+: A Video Quality Assessment Model for Exposure Correction with Vision-Language Guidance
May 7, 2024, 4:48 a.m. | Xunchu Zhou, Xiaohong Liu, Yunlong Dong, Tengchuan Kou, Yixuan Gao, Zicheng Zhang, Chunyi Li, Haoning Wu, Guangtao Zhai
cs.CV updates on arXiv.org arxiv.org
Abstract: Recently, User-Generated Content (UGC) videos have gained popularity in our daily lives. However, UGC videos often suffer from poor exposure due to the limitations of photographic equipment and techniques. Therefore, Video Exposure Correction (VEC) algorithms have been proposed, Low-Light Video Enhancement (LLVE) and Over-Exposed Video Recovery (OEVR) included. Equally important to the VEC is the Video Quality Assessment (VQA). Unfortunately, almost all existing VQA models are built generally, measuring the quality of a video from …
abstract algorithms arxiv assessment cs.cv daily equipment generated guidance however language light limitations low quality type ugc video video quality videos vision vision-language vqa
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