Introduces EPIC-Contact dataset and HOPformer transformer for in-the-wild egocentric 3D hand-object pose estimation, reporting 82.4% success on ARCTIC and doubled success with 75% lower contact error on the new dataset.
arXiv preprint arXiv:2501.08329 , year=
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EgoForce recovers absolute camera-space 3D hand pose from monocular egocentric images using forearm guidance, a unified arm-hand transformer, and a closed-form ray-space solver that handles fisheye, perspective, and wide-FOV cameras.
EggHand unifies VLA action decoding with viewpoint-aware video-text encoding to forecast egocentric hand poses, achieving SOTA accuracy on EgoExo4D while remaining robust to ego-motion and controllable via language prompts.
citing papers explorer
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Towards in-the-wild Egocentric 3D Hand-Object Pose Estimation
Introduces EPIC-Contact dataset and HOPformer transformer for in-the-wild egocentric 3D hand-object pose estimation, reporting 82.4% success on ARCTIC and doubled success with 75% lower contact error on the new dataset.
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EgoForce: Forearm-Guided Camera-Space 3D Hand Pose from a Monocular Egocentric Camera
EgoForce recovers absolute camera-space 3D hand pose from monocular egocentric images using forearm guidance, a unified arm-hand transformer, and a closed-form ray-space solver that handles fisheye, perspective, and wide-FOV cameras.
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EggHand: A Multimodal Foundation Model for Egocentric Hand Pose Forecasting
EggHand unifies VLA action decoding with viewpoint-aware video-text encoding to forecast egocentric hand poses, achieving SOTA accuracy on EgoExo4D while remaining robust to ego-motion and controllable via language prompts.