1 citations · 2 across the 8 of their papers we have counts for
7 papers · 1 filter
EgoExoMoCap: Distributed Ego-Exo Human Motion Capture
Jiaxi Jiang, Bharat Lal Bhatnagar, Nan Yang +6
Human motion capture from head-mounted devices (HMDs) offers a scalable way to acquire real-world human motion and interaction data, which is crucial for applications in embodied A…
GIRAF: Towards Generalizable Human Interactions with Articulated Objects
Xiaohan Zhang, Sebastian Starke, Alexander Winkler +3
Synthesizing realistic full-body human interactions with articulated objects is a fundamental challenge for embodied AI and graphics, with applications in robotics training and vir…
IMAGIN-4D: Image-Guided Controllable Interaction Generation
Sai Kumar Dwivedi, Federica Bogo, Buğra Tekin +6
Generating human-object interactions (HOI) is central to character animation, robotics, AR/VR, and embodied AI. Recent HOI generation methods synthesize motion from text, object ge…
NymeriaPlus: Enriching Nymeria Dataset with Additional Annotations and Data
Daniel DeTone, Federica Bogo, Eric-Tuan Le +7
The Nymeria Dataset, released in 2024, is a large-scale collection of in-the-wild human activities captured with multiple egocentric wearable devices that are spatially localized a…
Masked Modeling for Human Motion Recovery Under Occlusions
Zhiyin Qian, Siwei Zhang, Bharat Lal Bhatnagar +2
Human motion reconstruction from monocular videos is a fundamental challenge in computer vision, with broad applications in AR/VR, robotics, and digital content creation, but remai…
SplatFields: Neural Gaussian Splats for Sparse 3D and 4D Reconstruction
Marko Mihajlovic, Sergey Prokudin, Siyu Tang +4
Digitizing 3D static scenes and 4D dynamic events from multi-view images has long been a challenge in computer vision and graphics. Recently, 3D Gaussian Splatting (3DGS) has emerg…
RoHM: Robust Human Motion Reconstruction via Diffusion
Siwei Zhang, Bharat Lal Bhatnagar, Yuanlu Xu +4
We propose RoHM, an approach for robust 3D human motion reconstruction from monocular RGB(-D) videos in the presence of noise and occlusions. Most previous approaches either train…