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correct wrong links on BUFFER #13

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correct wrong links on BUFFER #13

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2 changes: 1 addition & 1 deletion README.md
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Expand Up @@ -1067,7 +1067,7 @@ Statistics: :fire: code is available & stars >= 100  |  :star: citatio
- [[CVPR](https://arxiv.org/abs/2304.09446)] Density-Insensitive Unsupervised Domain Adaption on 3D Object Detection. [[code](https://github.com/WoodwindHu/DTS)] [__`Detection`__]
- [[CVPR](https://arxiv.org/abs/2304.04248)] Curricular Object Manipulation in LiDAR-based Object Detection. [[code](https://github.com/ZZY816/COM)] [__`Detection`__]
- [[CVPR](https://arxiv.org/abs/2303.09950)] Deep Graph-based Spatial Consistency for Robust Non-rigid Point Cloud Registration. [[code](https://github.com/qinzheng93/GraphSCNet)] [__`Registration`__]
- [[CVPR](https://arxiv.org/abs/2303.09950)] BUFFER: Balancing Accuracy, Efficiency, and Generalizability in Point Cloud Registration. [[code](https://github.com/qinzheng93/GraphSCNet)] [__`Registration`__]
- [[CVPR](https://openaccess.thecvf.com/content/CVPR2023/html/Ao_BUFFER_Balancing_Accuracy_Efficiency_and_Generalizability_in_Point_Cloud_Registration_CVPR_2023_paper.html)] BUFFER: Balancing Accuracy, Efficiency, and Generalizability in Point Cloud Registration. [[code](https://github.com/The-Learning-And-Vision-Atelier-LAVA/BUFFER)] [__`Registration`__]
- [[CVPR](https://arxiv.org/abs/2212.06785)] Learning 3D Representations from 2D Pre-trained Models via Image-to-Point Masked Autoencoders. [[code](https://github.com/ZrrSkywalker/I2P-MAE)] [__`Representations`__]
- [[CVPR](https://arxiv.org/pdf/2303.08134.pdf)] Parameter is Not All You Need: Starting from Non-Parametric Networks for 3D Point Cloud Analysis. [[code](https://github.com/ZrrSkywalker/Point-NN)] [__`Representations`__]
- [[CVPR](https://github.com/thu-ml/3D_Corruptions_AD)] Benchmarking Robustness of 3D Object Detection to Common Corruptions in Autonomous Driving. [[code](https://github.com/thu-ml/3D_Corruptions_AD)] [__`Benchmark`__]
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