Synthetic image dataset (1.6 million images) with bodies in motion in realistic environments and trained HPS regressors using only this data. BEDLAM dataset contains monocular RGB videos with ground-truth 3D bodies in SMPL-X format. It includes a diversity of body shapes, motions, skin tones, hair, and clothing. The clothing is realistically simulated on the moving bodies using commercial clothing physics simulation. We render varying numbers of people in realistic scenes with varied lighting and camera motions. We then train various HPS regressors using BEDLAM and achieve state-of-the-art accuracy on real-image benchmarks despite training with synthetic data.

Code (ML): https://github.com/pixelite1201/BEDLAM
Code (render): https://github.com/PerceivingSystems/bedlam_render