Jeff Tan,
Donglai Xiang,
Shubham Tulsiani,
Deva Ramanan,
Gengshan Yang
Abstract: Given a single input video of a human, DressRecon reconstructs a time-consistent 4D body model, including shape, appearance, time-varying body articulations, as well as extremely loose clothing deformation or accessory objects. We propose a hierarchical bag-of-bones deformation model that allows body and clothing motion to be separated. We leverage image-based priors such as human body pose, surface normals, and optical flow to make optimization more tractable. The resulting neural fields can be extracted into time-consistent meshes, or further optimized as explicit 3D Gaussians for high-fidelity interactive rendering.