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FoundHand is trained on our large-scale FoundHand-10M dataset which contains automatically extracted 2D keypoints and segmentation mask annotations (top left). FoundHand is formulated as a 2D pose-conditioned image-to-image diffusion model that enables precise hand pose and camera viewpoint control (top right). Optionally, we can condition the generation with a reference image to preserve its style (top right). Our model demonstrates exceptional in-the-wild generalization across hand-centric applications and has core capabilities. such as gesture transfer, domain transfer, and novel view synthesis (middle row). This endows FoundHand with zero-shot applications to fix malformed hand images and synthesize coherent hand and hand-object videos, without explicitly giving object cues (bottom row).
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Predicting Camera Viewpoint Improves Cross-dataset Generalization for 3D Human Pose Estimation
Monocular estimation of 3d human pose has attracted in- creased attention with the availability of large ground-truth motion capture datasets. However, the diversity of training data available is limited and it is not clear to what extent methods generalize outside the specific datasets they are trained on. In this work we carry out a systematic study of the diversity and biases present in specific datasets and its e↵ect on cross-dataset generalization across a compendium of 5 pose datasets. We specifically focus on systematic di↵erences in the distri- bution of camera viewpoints relative to a body-centered coordinate frame. Based on this observation, we propose an auxiliary task of predicting the camera viewpoint in addition to pose. We find that models trained to jointly predict viewpoint and pose systematically show significantly improved cross-dataset generalization.
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- Award ID(s):
- 1813785
- PAR ID:
- 10296118
- Date Published:
- Journal Name:
- IEEE International Conference on Computer Vision workshops
- ISSN:
- 2473-9936
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Accepted Manuscript1.0
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- The DOI is not currently available.
