5 papers
MAMMA: Markerless & Automatic Multi-Person Motion Action Capture
Hanz Cuevas-Velasquez, Anastasios Yiannakidis, Soyong Shin +7
We present MAMMA, a markerless motion-capture pipeline that accurately recovers SMPL-X parameters from multi-view video of two-person interaction sequences. Traditional motion-capt…
Ground Reaction Inertial Poser: Physics-based Human Motion Capture from Sparse IMUs and Insole Pressure Sensors
Ryosuke Hori, Jyun-Ting Song, Zhengyi Luo +4
We propose Ground Reaction Inertial Poser (GRIP), a method that reconstructs physically plausible human motion using four wearable devices. Unlike conventional IMU-only approaches,…
DuoMo: Dual Motion Diffusion for World-Space Human Reconstruction
Yufu Wang, Evonne Ng, Soyong Shin +8
We present DuoMo, a generative method that recovers human motion in world-space coordinates from unconstrained videos with noisy or incomplete observations. Reconstructing such mot…
SAM 3D Body: Robust Full-Body Human Mesh Recovery
Xitong Yang, Devansh Kukreja, Don Pinkus +11
We introduce SAM 3D Body (3DB), a promptable model for single-image full-body 3D human mesh recovery (HMR) that demonstrates state-of-the-art performance, with strong generalizatio…
From Skin to Skeleton: Towards Biomechanically Accurate 3D Digital Humans
Marilyn Keller, Keenon Werling, Soyong Shin +4
Great progress has been made in estimating 3D human pose and shape from images and video by training neural networks to directly regress the parameters of parametric human models l…