69 citations · 87 across the 7 of their papers we have counts for
6 papers · 1 filter
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…
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…
WHAM: Reconstructing World-grounded Humans with Accurate 3D Motion
Soyong Shin, Juyong Kim, Eni Halilaj +1
The estimation of 3D human motion from video has progressed rapidly but current methods still have several key limitations. First, most methods estimate the human in camera coordin…
Multi-view Human Pose and Shape Estimation Using Learnable Volumetric Aggregation
Soyong Shin, Eni Halilaj
Human pose and shape estimation from RGB images is a highly sought after alternative to marker-based motion capture, which is laborious, requires expensive equipment, and constrain…