4 citations · 4 across the 7 of their papers we have counts for
7 papers
EgoPoseFormer v2: Accurate Egocentric Human Motion Estimation for AR/VR
Zhenyu Li, Sai Kumar Dwivedi, Filip Maric +11
Egocentric human motion estimation is essential for AR/VR experiences, yet remains challenging due to limited body coverage from the egocentric viewpoint, frequent occlusions, and…
PALM: A Dataset and Baseline for Learning Multi-subject Hand Prior
Zicong Fan, Edoardo Remelli, David Dimond +5
The ability to grasp objects, signal with gestures, and share emotion through touch all stem from the unique capabilities of human hands. Yet creating high-quality personalized han…
Geometric Neural Distance Fields for Learning Human Motion Priors
Zhengdi Yu, Simone Foti, Linguang Zhang +4
We introduce Neural Riemannian Motion Fields (NRMF), a novel 3D generative human motion prior that enables robust, temporally consistent, and physically plausible 3D motion recover…
GoTrack: Generic 6DoF Object Pose Refinement and Tracking
Van Nguyen Nguyen, Christian Forster, Sindi Shkodrani +4
We introduce GoTrack, an efficient and accurate CAD-based method for 6DoF object pose refinement and tracking, which can handle diverse objects without any object-specific training…
FoundHand: Large-Scale Domain-Specific Learning for Controllable Hand Image Generation
Kefan Chen, Chaerin Min, Linguang Zhang +3
Despite remarkable progress in image generation models, generating realistic hands remains a persistent challenge due to their complex articulation, varying viewpoints, and frequen…
EgoPoseFormer: A Simple Baseline for Stereo Egocentric 3D Human Pose Estimation
Chenhongyi Yang, Anastasia Tkach, Shreyas Hampali +3
We present EgoPoseFormer, a simple yet effective transformer-based model for stereo egocentric human pose estimation. The main challenge in egocentric pose estimation is overcoming…
FoundPose: Unseen Object Pose Estimation with Foundation Features
Evin Pınar Örnek, Yann Labbé, Bugra Tekin +4
We propose FoundPose, a model-based method for 6D pose estimation of unseen objects from a single RGB image. The method can quickly onboard new objects using their 3D models withou…