Recently, we have released a lightweight Cylinder3D model with much higher performance here. In this codebase, the reproduced Cylinder3D model is 2.9 point higher than the original Cylinder3D model in SemanticKITTI test set (single-scan). Besides, the released models achieve competitive performance in three benchmarks, i.e., ranks 1st in Waymo 3D Semantic Segmentation Challenge, ranks 1st in SemanticKITTI LiDAR Semantic Segmentation Challenge (single-scan) and ranks 2nd in SemanticKITTI LiDAR Semantic Segmentation Challenge (multi-scan). The trained model has been used in one NeurIPS 2022 submission! More LiDAR semantic segmentation models will be supported in the future. Do not hesitate to use the trained models!
Recently, we have released a lightweight Cylinder3D model with much higher performance here. In this codebase, the reproduced Cylinder3D model is 2.9 point higher than the original Cylinder3D model in SemanticKITTI test set (single-scan). Besides, the released models achieve competitive performance in three benchmarks, i.e., ranks 1st in Waymo 3D Semantic Segmentation Challenge, ranks 1st in SemanticKITTI LiDAR Semantic Segmentation Challenge (single-scan) and ranks 2nd in SemanticKITTI LiDAR Semantic Segmentation Challenge (multi-scan). The trained model has been used in one NeurIPS 2022 submission! More LiDAR semantic segmentation models will be supported in the future. Do not hesitate to use the trained models!