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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Papers and Datasets about Point Cloud.
| Date | Stars |
|---|---|
| 2026-07-24 | 2933 |
| 2026-07-25 | 2933 |
| 2026-07-28 | 2933 |
| 2026-07-30 | 2933 |
| 2026-08-06 | 2933 |
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# 3D - Point Cloud **Paper list** and **Datasets** about Point Cloud. Datasets can be found in [Datasets.md](https://github.com/zhulf0804/3D-PointCloud/blob/master/Datasets.md). <hr /> ## Survey papers - [A Comprehensive Survey and Taxonomy on Point Cloud Registration Based on Deep Learning](https://arxiv.org/pdf/2404.13830v1.pdf) [IJCAI 2024; [Github](https://github.com/yxzhang15/PCR)] - [Sequential Point Clouds: A Survey](https://arxiv.org/pdf/2204.09337.pdf) [TPAMI 2024] - [A Survey of Label-Efficient Deep Learning for 3D Point Clouds](https://arxiv.org/pdf/2305.19812.pdf) [TPAMI 2024; [Github](https://github.com/xiaoaoran/3D_label_efficient_learning)] - [Surface Reconstruction from Point Clouds: A Survey and a Benchmark](https://arxiv.org/pdf/2205.02413.pdf) [TPAMI 2024] - [End-to-end Autonomous Driving: Challenges and Frontiers](https://arxiv.org/pdf/2306.16927.pdf) [TPAMI 2024; [Github](https://github.com/OpenDriveLab/End-to-end-Autonomous-Driving)] - [3D Object Detection for Autonomous Driving: A Comprehensive Survey](https://arxiv.org/pdf/2206.09474.pdf) [IJCV 2023; [Github](https://github.com/pointscoder/awesome-3d-object-detection-for-autonomous-driving)] - [Unsupervised Point Cloud Representation Learning with Deep Neural Networks: A Survey](https://arxiv.org/pdf/2202.13589.pdf) [TPAMI 2023; [Github](https://github.com/xiaoaoran/3d_url_survey)] - [3D Object Detection from Images for Autonomous Driving: A Survey](https://arxiv.org/pdf/2202.02980.pdf) [TPAMI 2023; [Github](https://github.com/xinzhuma/3dodi-survey)] - [Survey and Systematization of 3D Object Detection Models and Methods](https://arxiv.org/pdf/2201.09354v1.pdf) [TVC 2023] - [Multi-Modal 3D Object Detection in Autonomous Driving: a Survey](https://arxiv.org/pdf/2106.12735.pdf) [IJCV 2023] - [Cross-source Point Cloud Registration: Challenges, Progress and Prospects](https://arxiv.org/pdf/2305.13570.pdf) [Neurocomputing 2023] - [Self-Supervised Learning for Point Clouds Data: A Survey](https://arxiv.org/pdf/2305.11881.pdf) [ESWA 2023] - [Self-supervised Learning for Pre-Training 3D Point Clouds: A Survey](https://arxiv.org/pdf/2305.04691.pdf) [arXiv 2023] - [Radar-Camera Fusion for Object Detection and Semantic Segmentation in Autonomous Driving: A Comprehensive Review](https://arxiv.org/pdf/2304.10410v2.pdf) [IEEE T-IV 2023; [Project](https://radar-camera-fusion.github.io)] - [Perception Datasets for Anomaly Detection in Autonomous Driving: A Survey](https://arxiv.org/pdf/2302.02790.pdf) [IEEE T-IV 2023] - [Delving into the Devils of Bird's-eye-view Perception: A Review, Evaluation and Recipe](https://arxiv.org/pdf/2209.05324.pdf) [TPAMI 2023; [Github](https://github.com/OpenDriveLab/BEVPerception-Survey-Recipe)] - [3D Vision with Transformers: A Survey](https://arxiv.org/pdf/2208.04309.pdf) [arXiv 2022; [Github](https://github.com/lahoud/3d-vision-transformers)] - [Vision-Centric BEV Perception: A Survey](https://arxiv.org/pdf/2208.02797.pdf) [arXiv 2022; [Github](https://github.com/4DVLab/Vision-Centric-BEV-Perception)] - [Transformers in 3D Point Clouds: A Survey](https://arxiv.org/pdf/2205.07417.pdf) [arXiv 2022] - [A Survey of Robust LiDAR-based 3D Object Detection Methods for Autonomous Driving](https://arxiv.org/pdf/2204.00106.pdf) [arXiv 2022] - [A Survey of Non-Rigid 3D Registration](https://arxiv.org/pdf/2203.07858.pdf) [Eurographics 2022] - [Comprehensive Review of Deep Learning-Based 3D Point Clouds Completion Processing and Analysis](https://arxiv.org/pdf/2203.03311.pdf) [TITS 2022] - [Multi-modal Sensor Fusion for Auto Driving Perception: A Survey](https://arxiv.org/pdf/2202.02703.pdf) [arXiv 2022] - [3D Object Detection for Autonomous Driving: A Survey](https://arxiv.org/pdf/2106.10823.pdf) [Pattern Recognition 2022; [Github](https://github.com/rui-qian/SoTA-3D-Object-Detection)] - [3D Semantic Scene Completion: a Survey](https://arxiv.org/pdf/2103.07466.pdf) [IJCV 2022] - [Deep Learning based 3D Segmentation: A Survey](https://arxiv.or
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Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:6c432f92e90ff3b5, topic:datasets, desc:datasets, readme:datasets
matched fp:6c432f92e90ff3b5, topic:autonomous-driving, readme:autonomous driving
matched fp:6c432f92e90ff3b5, topic:papers, readme:paper list
