1 code implementation • CVPR 2025 • Yufu Wang, Yu Sun, Priyanka Patel, Kostas Daniilidis, Michael J. Black, Muhammed Kocabas
Human pose and shape (HPS) estimation presents challenges in diverse scenarios such as crowded scenes, person-person interactions, and single-view reconstruction.
no code implementations • 13 Nov 2024 • Hanz Cuevas-Velasquez, Priyanka Patel, Haiwen Feng, Michael Black
While BEDLAM demonstrates the potential of traditional procedural graphics to generate such data, the training images are clearly synthetic.
2 code implementations • 12 Nov 2024 • Priyanka Patel, Michael J. Black
We use the estimated intrinsics to enhance the 4D-Humans dataset by incorporating a full perspective camera model during SMPLify fitting.
1 code implementation • CVPR 2024 • Sai Kumar Dwivedi, Yu Sun, Priyanka Patel, Yao Feng, Michael J. Black
We address the problem of regressing 3D human pose and shape from a single image, with a focus on 3D accuracy.
Ranked #36 on
3D Human Pose Estimation
on 3DPW
no code implementations • CVPR 2024 • Yao Feng, Jing Lin, Sai Kumar Dwivedi, Yu Sun, Priyanka Patel, Michael J. Black
Additionally, ChatPose empowers LLMs to apply their extensive world knowledge in reasoning about human poses, leading to two advanced tasks: speculative pose generation and reasoning about pose estimation.
2 code implementations • CVPR 2023 • Michael J. Black, Priyanka Patel, Joachim Tesch, Jinlong Yang
BEDLAM is useful for a variety of tasks and all images, ground truth bodies, 3D clothing, support code, and more are available for research purposes.
1 code implementation • CVPR 2021 • Priyanka Patel, Chun-Hao P. Huang, Joachim Tesch, David T. Hoffmann, Shashank Tripathi, Michael J. Black
Additionally, we fine-tune methods on AGORA and show improved performance on both AGORA and 3DPW, confirming the realism of the dataset.