6 papers
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…
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…
TS-Diff: Two-Stage Diffusion Model for Low-Light RAW Image Enhancement
Yi Li, Zhiyuan Zhang, Jiangnan Xia +5
This paper presents a novel Two-Stage Diffusion Model (TS-Diff) for enhancing extremely low-light RAW images. In the pre-training stage, TS-Diff synthesizes noisy images by constru…
HDiffTG: A Lightweight Hybrid Diffusion-Transformer-GCN Architecture for 3D Human Pose Estimation
Yajie Fu, Chaorui Huang, Junwei Li +4
We propose HDiffTG, a novel 3D Human Pose Estimation (3DHPE) method that integrates Transformer, Graph Convolutional Network (GCN), and diffusion model into a unified framework. HD…
Learning Orientation Field for OSM-Guided Autonomous Navigation
Yuming Huang, Wei Gao, Zhiyuan Zhang +4
OpenStreetMap (OSM) has gained popularity recently in autonomous navigation due to its public accessibility, lower maintenance costs, and broader geographical coverage. However, ex…
Night-Rider: Nocturnal Vision-aided Localization in Streetlight Maps Using Invariant Extended Kalman Filtering
Tianxiao Gao, Mingle Zhao, Chengzhong Xu +1
Vision-aided localization for low-cost mobile robots in diverse environments has attracted widespread attention recently. Although many current systems are applicable in daytime en…