3 papers
cs.CV2026
Empowering Feed-Forward Reconstruction Models with Metric Scale via Satellite Images
Xianghui Ze, Yongjian Luo, Mengjun Chao +3
Feed-forward 3D reconstruction models have recently shown strong generalization across diverse scenes, yet most of them recover geometry only up to an unknown global scale. This sc…
cs.RO2025
Efficient Active Training for Deep LiDAR Odometry
Beibei Zhou, Zhiyuan Zhang, Zhenbo Song +2
Robust and efficient deep LiDAR odometry models are crucial for accurate localization and 3D reconstruction, but typically require extensive and diverse training data to adapt to d…
cs.RO2025
Generalizing Unsupervised Lidar Odometry Model from Normal to Snowy Weather Conditions
Beibei Zhou, Zhiyuan Zhang, Zhenbo Song +2
Deep learning-based LiDAR odometry is crucial for autonomous driving and robotic navigation, yet its performance under adverse weather, especially snowfall, remains challenging. Ex…