AI RESEARCH
Identity-Preserving Image-to-Video Generation via Reward-Guided Optimization
arXiv CS.CV
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ArXi:2510.14255v4 Announce Type: replace Recent advances in image-to-video (I2V) generation have achieved remarkable progress in synthesizing high-quality, temporally coherent videos from static images. Among all the applications of I2V, human-centric video generation includes a large portion. However, existing I2V models encounter difficulties in maintaining identity consistency between the input human image and the generated video, especially when the person in the video exhibits significant expression changes and movements.