3 papers
cs.CV2025
BEDLAM2.0: Synthetic Humans and Cameras in Motion
Joachim Tesch, Giorgio Becherini, Prerana Achar +4
Inferring 3D human motion from video remains a challenging problem with many applications. While traditional methods estimate the human in image coordinates, many applications requ…
cs.CV2024
Toward Human Understanding with Controllable Synthesis
Hanz Cuevas-Velasquez, Priyanka Patel, Haiwen Feng +1
Training methods to perform robust 3D human pose and shape (HPS) estimation requires diverse training images with accurate ground truth. While BEDLAM demonstrates the potential of…
cs.CV2024
CameraHMR: Aligning People with Perspective
Priyanka Patel, Michael J. Black
We address the challenge of accurate 3D human pose and shape estimation from monocular images. The key to accuracy and robustness lies in high-quality training data. Existing train…