ClimbingCap: Multi-Modal Dataset and Method for Rock Climbing in World Coordinate
Ming Yan, Xincheng Lin, Yuhua Luo, Shuqi Fan, Yudi Dai, Qixin Zhong, Lincai Zhong, Yuexin Ma, Lan Xu, Chenglu Wen, Siqi Shen, Cheng Wang
Abstract
Dataset: AscendMotion No Markers With Markers World Coordinate 3D Scene Method: ClimbingCap RGB LiDAR Points RGB IMU LiDAR Points Figure 1. Overview. To address the challenging problem of global climbing motion recovery, we collect the dataset AscendMotion, using LiDAR, RGB camera and Inertial Measurement Unit (IMU) motion capture system with accurate motion labels and global trajectories (the blue and orange human bodies in right side of the figure represent labeled motions, and the orange curve represents the motion trajectory in the world coordinate.). Meanwhile, we propose ClimbingCap, a global climbing motion capturing method in world coordinate. As shown in the left part of this figure, it uses both image and LiDAR point cloud to recover human motions.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Cited by top-tier papers3
- Towards Motion Turing Test: Evaluating Human-Likeness in Humanoid RobotsMingzhe Li, Mengyin Liu, Zekai Wu, Xincheng Lin et al.CVPR 2026 · 4 citations
- FlashCap: Millisecond-Accurate Human Motion Capture via Flashing LEDs and Event-Based VisionZekai Wu, Shuqi Fan, Mengyin Liu, Yuhua Luo et al.CVPR 2026 · 2 citations
- MotionMAR: Multi-scale Auto-Regressive Human Motion Reconstruction from Sparse ObservationsYuhua Luo, Junsheng Zhang, Mengyin Liu, Xincheng Lin et al.ICML 2026
Builds on37
- An Image is Worth 16x16 Words: Transformers for Image Recognition at ScaleAlexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn et al.ICLR 2021 · 21,477 citations
- AMASS: Archive of Motion Capture As Surface ShapesNaureen Mahmood, Nima Ghorbani, Nikolaus F. Troje, Gerard Pons-Moll et al.ICCV 2019 · 1,784 citations
- PIFu: Pixel-Aligned Implicit Function for High-Resolution Clothed Human DigitizationShunsuke Saito, Zeng Huang, Ryota Natsume, Shigeo Morishima et al.ICCV 2019 · 1,411 citations
- Learning to Reconstruct 3D Human Pose and Shape via Model-Fitting in the LoopNikos Kolotouros, Georgios Pavlakos, Michael J. Black, Kostas DaniilidisICCV 2019 · 1,139 citations
- PARE: Part Attention Regressor for 3D Human Body EstimationMuhammed Kocabas, Chun-Hao P. Huang, Otmar Hilliges, Michael J. BlackICCV 2021 · 509 citations
Related papers
- CIMI4D: A Large Multimodal Climbing Motion Dataset under Human-scene InteractionsMing Yan, Xin Wang, Yudi Dai, Siqi Shen et al.CVPR 2023
- HSC4D: Human-centered 4D Scene Capture in Large-scale Indoor-outdoor Space Using Wearable IMUs and LiDARYudi Dai, Yitai Lin, Chenglu Wen, Siqi Shen et al.CVPR 2022 · 24 citations
- LiDARCap: Long-range Markerless 3D Human Motion Capture with LiDAR Point CloudsJialian Li, Jingyi Zhang, Zhiyong Wang, Siqi Shen et al.CVPR 2022 · 49 citations
- LiDAR-aid Inertial Poser: Large-scale Human Motion Capture by Sparse Inertial and LiDAR SensorsYiming Ren, Chengfeng Zhao, Yannan He, Peishan Cong et al.IEEE VR 2023 · 50 citations
- FreeCap: Hybrid Calibration-Free Motion Capture in Open EnvironmentsAoru Xue, Yiming Ren, Zining Song, Mao Ye et al.AAAI 2025 · 4 citations
