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Found 7 papers, 5 papers with code
PromptHMR: Promptable Human Mesh Recovery
Human pose and shape (HPS) estimation presents challenges in diverse scenarios such as crowded scenes, person-person interactions, and single-view reconstruction.
Toward Human Understanding with Controllable Synthesis
While BEDLAM demonstrates the potential of traditional procedural graphics to generate such data, the training images are clearly synthetic.
CameraHMR: Aligning People with Perspective
We use the estimated intrinsics to enhance the 4D-Humans dataset by incorporating a full perspective camera model during SMPLify fitting.
TokenHMR: Advancing Human Mesh Recovery with a Tokenized Pose Representation
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
ChatPose: Chatting about 3D Human Pose
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.
BEDLAM: A Synthetic Dataset of Bodies Exhibiting Detailed Lifelike Animated Motion
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.
AGORA: Avatars in Geography Optimized for Regression Analysis
Additionally, we fine-tune methods on AGORA and show improved performance on both AGORA and 3DPW, confirming the realism of the dataset.
