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AIS 2024 Challenge on Video Quality Assessment of User-Generated Content: Methods and Results
April 26, 2024, 4:44 a.m. | Marcos V. Conde, Saman Zadtootaghaj, Nabajeet Barman, Radu Timofte, Chenlong He, Qi Zheng, Ruoxi Zhu, Zhengzhong Tu, Haiqiang Wang, Xiangguang Chen, W
cs.CV updates on arXiv.org arxiv.org
Abstract: This paper reviews the AIS 2024 Video Quality Assessment (VQA) Challenge, focused on User-Generated Content (UGC). The aim of this challenge is to gather deep learning-based methods capable of estimating the perceptual quality of UGC videos. The user-generated videos from the YouTube UGC Dataset include diverse content (sports, games, lyrics, anime, etc.), quality and resolutions. The proposed methods must process 30 FHD frames under 1 second. In the challenge, a total of 102 participants registered, …
abstract aim arxiv assessment challenge cs.cv cs.mm deep learning gather generated paper quality results reviews type ugc video video quality videos vqa youtube
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