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João Pedro Araújo

2 accepted papers

2023

CIRCLE: Capture in Rich Contextual Environments

CVPR 2023poster

Synthesizing 3D human motion in a contextual, ecological environment is important for simulating realistic activities people perform in the real world. However, conventional optics-based motion capture systems are not suited for simultaneously capturing human movements and complex scenes. The lack o…

2023

NeMo: Learning 3D Neural Motion Fields From Multiple Video Instances of the Same Action

CVPR 2023highlight

The task of reconstructing 3D human motion has wide-ranging applications. The gold standard Motion capture (MoCap) systems are accurate but inaccessible to the general public due to their cost, hardware, and space constraints. In contrast, monocular human mesh recovery (HMR) methods are much more ac…

Cited by 9SourcePDFScholar