4 citations · 9 across the 6 of their papers we have counts for
6 papers
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…
HiSC4D: Human-centered interaction and 4D Scene Capture in Large-scale Space Using Wearable IMUs and LiDAR
Yudi Dai, Zhiyong Wang, Xiping Lin +5
We introduce HiSC4D, a novel Human-centered interaction and 4D Scene Capture method, aimed at accurately and efficiently creating a dynamic digital world, containing large-scale in…
RELI11D: A Comprehensive Multimodal Human Motion Dataset and Method
Ming Yan, Yan Zhang, Shuqiang Cai +8
Comprehensive capturing of human motions requires both accurate captures of complex poses and precise localization of the human within scenes. Most of the HPE datasets and methods…
CIMI4D: A Large Multimodal Climbing Motion Dataset under Human-scene Interactions
Ming Yan, Xin Wang, Yudi Dai +5
Motion capture is a long-standing research problem. Although it has been studied for decades, the majority of research focus on ground-based movements such as walking, sitting, dan…
SLOPER4D: A Scene-Aware Dataset for Global 4D Human Pose Estimation in Urban Environments
Yudi Dai, Yitai Lin, Xiping Lin +6
We present SLOPER4D, a novel scene-aware dataset collected in large urban environments to facilitate the research of global human pose estimation (GHPE) with human-scene interactio…
HSC4D: Human-centered 4D Scene Capture in Large-scale Indoor-outdoor Space Using Wearable IMUs and LiDAR
Yudi Dai, Yitai Lin, Chenglu Wen +5
We propose Human-centered 4D Scene Capture (HSC4D) to accurately and efficiently create a dynamic digital world, containing large-scale indoor-outdoor scenes, diverse human motions…