H-Flow learns dense human scene flow from monocular video via joint pose and depth prediction in a multi-head transformer, using physics-inspired geometric and biomechanical priors for self-supervision, and introduces the DynAct4D synthetic benchmark.
Smpl: a skinned multi-person linear model.ACM Transactions on Graphics (TOG), 34(6):1–16, 2015
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H-Flow: Self-supervised Human Scene Flow via Physics-inspired Joint Multi-modal Learning
H-Flow learns dense human scene flow from monocular video via joint pose and depth prediction in a multi-head transformer, using physics-inspired geometric and biomechanical priors for self-supervision, and introduces the DynAct4D synthetic benchmark.