17 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…
SOAR: Regression-based LiDAR Relocalization for UAVs
Hengyu Mu, Jianshi Wu, Yuxin Guo +5
Regression-based LiDAR relocalization has recently emerged as a promising solution for high-precision positioning in GNSS-denied environments. However, these methods are primarily…
LEADER: Learning Reliable Local-to-Global Correspondences for LiDAR Relocalization
Jianshi Wu, Minghang Zhu, Dunqiang Liu +5
LiDAR relocalization has attracted increasing attention as it can deliver accurate 6-DoF pose estimation in complex 3D environments. Recent learning-based regression methods offer…
V2U4Real: A Real-world Large-scale Dataset for Vehicle-to-UAV Cooperative Perception
Weijia Li, Haoen Xiang, Tianxu Wang +4
Modern autonomous vehicle perception systems are often constrained by occlusions, blind spots, and limited sensing range. While existing cooperative perception paradigms, such as V…
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…
AW-MoE: All-Weather Mixture of Experts for Robust Multi-Modal 3D Object Detection
Hongwei Lin, Xun Huang, Chenglu Wen +1
Robust 3D object detection under adverse weather conditions is crucial for autonomous driving. However, most existing methods simply combine all weather samples for training while…