Jiachao Gong — accepted AI-conference papers

2026

Score2Instruct: Scaling Up Video Quality-Centric Instructions via Automated Dimension Scoring

Qizhi Xie, Kun Yuan, Yunpeng Qu, Jiachao Gong, Mingda Wu, Ming Sun +2

CVPR 2026

Classical video quality assessment (VQA) methods generate a numerical score to judge a video's perceived visual fidelity and clarity. Yet, a score fails to describe the video's complex quality dimensions (e.g., noise), restricting its applicability. Benefiting from the human-friendly linguistic outp

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2024

PTM-VQA: Efficient Video Quality Assessment Leveraging Diverse PreTrained Models from the Wild

Kun Yuan, Hongbo Liu, Mading Li, Muyi Sun, Ming Sun, Jiachao Gong +3

CVPR 2024poster

Video quality assessment (VQA) is a challenging problem due to the numerous factors that can affect the perceptual quality of a video e.g. content attractiveness distortion type motion pattern and level. However annotating the Mean opinion score (MOS) for videos is expensive and time-consuming which…

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