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cs.RO2024
SGLC: Semantic Graph-Guided Coarse-Fine-Refine Full Loop Closing for LiDAR SLAM
Neng Wang, Xieyuanli Chen, Chenghao Shi +3
Loop closing is a crucial component in SLAM that helps eliminate accumulated errors through two main steps: loop detection and loop pose correction. The first step determines wheth…
cs.CV2024★ 4 cited
SegNet4D: Efficient Instance-Aware 4D Semantic Segmentation for LiDAR Point Cloud
Neng Wang, Ruibin Guo, Chenghao Shi +5
4D LiDAR semantic segmentation, also referred to as multi-scan semantic segmentation, plays a crucial role in enhancing the environmental understanding capabilities of autonomous v…
cs.CV2024
Diffusion-Based Point Cloud Super-Resolution for mmWave Radar Data
Kai Luan, Chenghao Shi, Neng Wang +3
The millimeter-wave radar sensor maintains stable performance under adverse environmental conditions, making it a promising solution for all-weather perception tasks, such as outdo…