Drag-based image editing provides an intuitive interface for spatially controlled image manipulation by allowing users to specify handle and target points. Existing methods have made substantial progress through optimization-based, one-step, and feed-forward formulations, but they often interpret drag instructions as g...
Armando Fortes, Tian-Yi Wei, Chindanai Trakantannarong et al.· 0 citations
This work proposes Hybrid-Policy Self-Distillation (HPSD), a novel self-distillation framework where a single TI2V model acts as both teacher and student under different conditions: the teacher operates in TI2V mode with a high-quality first frame and an enhanced prompt, while the student runs in the base T2V mode with...
Jia-Zi Bu, Peng-Yang Ling, Yu-Jie Zhou et al.· 2 citations
4D hand motion reconstruction from egocentric video is bottlenecked by clear limitations of existing methods: image-based pipelines depend on a detector that fails under heavy occlusion, while video-based methods rely on temporal modules learned only from scarce hand-pose annotations, a narrow signal insufficient to mo...
Yuxi Wang, Chengkai Jin, Yufei Liu et al.· arXiv.org· 1 citation· ⚡1
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