6 papers
XGrid-Mapping: Explicit Implicit Hybrid Grid Submaps for Efficient Incremental Neural LiDAR Mapping
Zeqing Song, Zhongmiao Yan, Junyuan Deng +5
Large-scale incremental mapping is fundamental to the development of robust and reliable autonomous systems, as it underpins incremental environmental understanding with sequential…
RadarLLM: Empowering Large Language Models to Understand Human Motion from Millimeter-Wave Point Cloud Sequence
Zengyuan Lai, Jiarui Yang, Songpengcheng Xia +6
Millimeter-wave radar offers a privacy-preserving and environment-robust alternative to vision-based sensing, enabling human motion analysis in challenging conditions such as low l…
EnvPoser: Environment-aware Realistic Human Motion Estimation from Sparse Observations with Uncertainty Modeling
Songpengcheng Xia, Yu Zhang, Zhuo Su +7
Estimating full-body motion using the tracking signals of head and hands from VR devices holds great potential for various applications. However, the sparsity and unique distributi…
mmDEAR: mmWave Point Cloud Density Enhancement for Accurate Human Body Reconstruction
Jiarui Yang, Songpengcheng Xia, Zengyuan Lai +4
Millimeter-wave (mmWave) radar offers robust sensing capabilities in diverse environments, making it a highly promising solution for human body reconstruction due to its privacy-fr…
360Recon: An Accurate Reconstruction Method Based on Depth Fusion from 360 Images
Zhongmiao Yan, Qi Wu, Songpengcheng Xia +4
360-degree images offer a significantly wider field of view compared to traditional pinhole cameras, enabling sparse sampling and dense 3D reconstruction in low-texture environment…
Suite-IN: Aggregating Motion Features from Apple Suite for Robust Inertial Navigation
Lan Sun, Songpengcheng Xia, Junyuan Deng +4
With the rapid development of wearable technology, devices like smartphones, smartwatches, and headphones equipped with IMUs have become essential for applications such as pedestri…