LiDAR localization is a fundamental task in robotics and computer vision, which estimates the pose of a Li-. DAR point cloud within a global map.

Nov 12, 2024 · We introduce LiSA, the first method that incorporates semantic aware-ness into SCR to boost the localization robustness and accuracy.

We use SphereFormer for data preprocessing (just used for training) and generate corresponding semantic feature. You need to download the code, put dataset.py ...

LiDAR localization is a fundamental task in robotics and computer vision, which estimates the pose of a Li-. DAR point cloud within a global map.

We introduce LiSA, the first method that incorporates semantic aware-ness into SCR to boost the localization robustness and accuracy.

Jul 31, 2024 · LiSA is the first method that incorporates semantic awareness into scene coordinate regression (SCR) to boost the localization robustness and accuracy in LiDAR ...

Experi-ments show the superior performance of LiSA on standard LiDAR localization benchmarks compared to state-of-the- art methods. Applying ...

LiSA：LiDAR Localization with Semantic Awareness. CVPR 2024. pdf. 代码. bibtex ... SemanticFlow: Semantic Segmentation of Sequential LiDAR Point Clouds from Sparse ...

LiSA: LiDAR Localization with Semantic Awareness. B Yang, Z Li, W Li, Z Cai, C Wen, Y Zang, M Muller, C Wang. Proceedings of the IEEE/CVF Conference on ...

Missing: Awareness. | Show results with:Awareness.