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Hi @vasgaowei, thanks for meticulously maintaining this informative repository!
To further enhance the comprehensiveness of this repository, I would like to recommend the following papers under the category BEV Segmentation - Lidar:
- FRNet: Frustum-Range Networks for Scalable LiDAR Segmentation (arXiv 2023) [Paper] [GitHub]
- Segment Any Point Cloud Sequences by Distilling Vision Foundation Models (NeurIPS 2023 Spotlight) [Paper] [GitHub]
- Towards Label-Free Scene Understanding by Vision Foundation Models (NeurIPS 2023) [Paper] [GitHub]
- Robo3D: Towards Robust and Reliable 3D Perception against Corruptions (ICCV 2023) [Paper] [GitHub]
- Rethinking Range View Representation for LiDAR Segmentation (ICCV 2023) [Paper]
- UniSeg: A Unified Multi-Modal LiDAR Segmentation Network and the OpenPCSeg Codebase (ICCV 2023) [Paper] [GitHub]
- LaserMix for Semi-Supervised LiDAR Semantic Segmentation (CVPR 2023 Highlight) [Paper] [GitHub]
- CLIP2Scene: Towards Label-Efficient 3D Scene Understanding by CLIP (CVPR 2023) [Paper] [GitHub]
- ConDA: Unsupervised Domain Adaptation for LiDAR Segmentation via Regularized Domain Concatenation (ICRA 2023) [Paper] [GitHub]
Also the following paper under the category 3D Object Detection - Multiple Camera:
- Benchmarking and Analyzing Bird's Eye View Perception Robustness to Corruptions (arXiv 2023) [Paper] [GitHub]
Thanks again for your help!
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