We present FlowHMR, a framework for recovering physically plausible global 3D human motion from monocular video. Previous learning-based methods typically regress human motion directly from video and train the network with geometric supervision. However, recovering human motion from monocular video is inherently ambigu...
Zhan-Ke Wang, Cheng-Feng Zhao, Qing Shuai et al.· 0 citations
AnimateCanvas is proposed, a model that supports cue-conditioned implicit motion planning to faithfully and coherently connect all cues, dense or sparse, full or partial, into one full-body motion sequence, and achieves state-of-the-art results in temporal completion, spatial control, sequential generation, language-gu...
Ze-Yu Ling, Di Kang, Qing Shuai et al.· 0 citations
Professional character animation requires both natural motion and precise, versatile control. For example, it is common for the creators to define the timing of a specified action, to control the motion range of the character's arm swing, and the route the character walks through, like specifying various kinematic moti...
Ze-Yu Ling, Di Kang, Qing Shuai et al.· 0 citations
MoRoute is introduced, a unified multimodal video generation framework that formulates a frozen VLM and a pretrained video DiT with different architectures as heterogeneous experts connected through dynamic layer routing.
Chong Gao, Jie Ma, Zhan Peng et al.· arXiv.org· 0 citations
The Identity-conditioned Queries task is introduced, in which models are required to jointly associate and interpret an input video and a reference image of a person, and leverage this conditioning to address identity grounding, behavior understanding, and temporal reasoning, among other challenges.
Shibo Gao, Chongxiao Wang, Chenglong Huang et al.· 0 citations
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