Identity-Preserving Video Generation Challenge

Yingwei Pan, Yiheng Zhang, Zhaofan Qiu, Ting Yao, Tao Mei

Keywords: Identity-Preserving Video Generation, AIGC

Abstract: This year's Identity-Preserving Video Generation Challenge (IPVG) includes two tracks: Facial Identity-Preserving Video Generation and Sequential Action Identity-Preserving Video Generation. In general, the goal of this grand challenge is two-fold: (a) coalescing community effort around new challenging identity-preserving video generation datasets, and (b) offering a fertile ground for designing controllable generative models to facilitate precise identity binding in video generation, aiming to propel the field toward more accountable and user-steerable video synthesis systems.

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Submission Number: 3