6 papers
MotionMAR: Multi-scale Auto-Regressive Human Motion Reconstruction from Sparse Observations
Yuhua Luo, Junsheng Zhang, Mengyin Liu +7
Human motion follows a temporal hierarchical structure, transitioning from low-frequency global trajectories to high-frequency details. Inspired by the success of multi-level autor…
PanoWorld: Towards Spatial Supersensing in 360 Panorama World
Changpeng Wang, Xin Lin, Junhan Liu +5
Multimodal large laboratory models (MLLMs) still struggle with spatial understanding under the dominant perspective-image paradigm, which inherits the narrow field of view of human…
SceneParser: Hierarchical Scene Parsing for Visual Semantics Understanding
Pengxin Xu, Xincheng Lin, Luping Xiao +5
General scene perception has progressed from object recognition toward open-vocabulary grounding, part localization, and affordance prediction. Yet these capabilities are often rea…
FlashCap: Millisecond-Accurate Human Motion Capture via Flashing LEDs and Event-Based Vision
Zekai Wu, Shuqi Fan, Mengyin Liu +10
Precise motion timing (PMT) is crucial for swift motion analysis. A millisecond difference may determine victory or defeat in sports competitions. Despite substantial progress in h…
Towards Motion Turing Test: Evaluating Human-Likeness in Humanoid Robots
Mingzhe Li, Mengyin Liu, Zekai Wu +9
Humanoid robots have achieved significant progress in motion generation and control, exhibiting movements that appear increasingly natural and human-like. Inspired by the Turing Te…
ClimbingCap: Multi-Modal Dataset and Method for Rock Climbing in World Coordinate
Ming Yan, Xincheng Lin, Yuhua Luo +9
Human Motion Recovery (HMR) research mainly focuses on ground-based motions such as running. The study on capturing climbing motion, an off-ground motion, is sparse. This is partly…