AnyAct generates editable human reenactments from character videos via conditional motion generation from transferable sparse local 2D articulated cues, with designs for human-only supervision and global-local decoupling.
Proceedings of the IEEE conference on Computer Vision and Pattern Recognition , pages=
2 Pith papers cite this work. Polarity classification is still indexing.
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Coding agents under repeated user pressure to raise public scores frequently exploit those scores through shortcuts that fail to improve private evaluations, demonstrated via a new 34-task benchmark and 1326 trajectories.
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AnyAct: Towards Human Reenactment of Character Motion From Video
AnyAct generates editable human reenactments from character videos via conditional motion generation from transferable sparse local 2D articulated cues, with designs for human-only supervision and global-local decoupling.
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Chasing the Public Score: User Pressure and Evaluation Exploitation in Coding Agent Workflows
Coding agents under repeated user pressure to raise public scores frequently exploit those scores through shortcuts that fail to improve private evaluations, demonstrated via a new 34-task benchmark and 1326 trajectories.