motion capture
PulseAugur coverage of motion capture — every cluster mentioning motion capture across labs, papers, and developer communities, ranked by signal.
1 day(s) with sentiment data
-
New dataset targets sign language recognition in cars
Researchers have developed the In-Car Sign Language Corpus (ICSL), a new multi-modal dataset designed to advance sign language recognition (SLR) within confined spaces like vehicles. The dataset includes both high-preci…
-
ComplexMimic framework enhances human-scene interaction imitation in 3D
Researchers have developed ComplexMimic, a new framework designed to improve imitation learning for human-scene interactions in complex 3D environments. This method addresses the challenge of balancing accurate motion t…
-
New AI framework uses physics simulation for realistic Human-Object Interactions
Researchers have developed a new framework called \"Ours\" that uses a physics simulator to generate realistic Human-Object Interactions (HOI). This approach aims to overcome the limitations of current data-driven metho…
-
CalTennis dataset released for 3D human pose estimation research
Researchers have introduced CalTennis, a large-scale video dataset designed for evaluating monocular-to-3D human pose estimation. The dataset features over 11 million frames of tennis play from 40 players, captured usin…
-
New Graph Mamba Operator Simulates Particle Systems
Researchers have developed the Graph Mamba Operator (GraMO), a novel approach for simulating interacting particle systems. GraMO integrates state-space models with graph-based learning to simultaneously handle spatial i…
-
AI models learn physics of motion-to-radar spectrograms, study finds
Researchers have developed a new framework to assess whether data-driven models that convert motion capture data to radar spectrograms are learning the underlying physics. This framework uses two metrics to measure the …