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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 36 / No. 1: AAAI-22 Technical Tracks 1

SVGA-Net: Sparse Voxel-Graph Attention Network for 3D Object Detection from Point Clouds

February 1, 2023

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Authors

Qingdong He

University of Electronic Science and Technology of China


Zhengning Wang

University of Electronic Science and Technology of China


Hao Zeng

University of Electronic Science and Technology of China


Yi Zeng

University of Electronic Science and Technology of China


Yijun Liu

University of Electronic Science and Technology of China


DOI:

10.1609/aaai.v36i1.19969


Abstract:

Accurate 3D object detection from point clouds has become a crucial component in autonomous driving. However, the volumetric representations and the projection methods in previous works fail to establish the relationships between the local point sets. In this paper, we propose Sparse Voxel-Graph Attention Network (SVGA-Net), a novel end-to-end trainable network which mainly contains voxel-graph module and sparse-to-dense regression module to achieve comparable 3D detection tasks from raw LIDAR data. Specifically, SVGA-Net constructs the local complete graph within each divided 3D spherical voxel and global KNN graph through all voxels. The local and global graphs serve as the attention mechanism to enhance the extracted features. In addition, the novel sparse-to-dense regression module enhances the 3D box estimation accuracy through feature maps aggregation at different levels. Experiments on KITTI detection benchmark and Waymo Open dataset demonstrate the efficiency of extending the graph representation to 3D object detection and the proposed SVGA-Net can achieve decent detection accuracy.

Topics: AAAI

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HOW TO CITE:

Qingdong He||Zhengning Wang||Hao Zeng||Yi Zeng||Yijun Liu SVGA-Net: Sparse Voxel-Graph Attention Network for 3D Object Detection from Point Clouds Proceedings of the AAAI Conference on Artificial Intelligence (2022) 870-878.

Qingdong He||Zhengning Wang||Hao Zeng||Yi Zeng||Yijun Liu SVGA-Net: Sparse Voxel-Graph Attention Network for 3D Object Detection from Point Clouds AAAI 2022, 870-878.

Qingdong He||Zhengning Wang||Hao Zeng||Yi Zeng||Yijun Liu (2022). SVGA-Net: Sparse Voxel-Graph Attention Network for 3D Object Detection from Point Clouds. Proceedings of the AAAI Conference on Artificial Intelligence, 870-878.

Qingdong He||Zhengning Wang||Hao Zeng||Yi Zeng||Yijun Liu. SVGA-Net: Sparse Voxel-Graph Attention Network for 3D Object Detection from Point Clouds. Proceedings of the AAAI Conference on Artificial Intelligence 2022 p.870-878.

Qingdong He||Zhengning Wang||Hao Zeng||Yi Zeng||Yijun Liu. 2022. SVGA-Net: Sparse Voxel-Graph Attention Network for 3D Object Detection from Point Clouds. "Proceedings of the AAAI Conference on Artificial Intelligence". 870-878.

Qingdong He||Zhengning Wang||Hao Zeng||Yi Zeng||Yijun Liu. (2022) "SVGA-Net: Sparse Voxel-Graph Attention Network for 3D Object Detection from Point Clouds", Proceedings of the AAAI Conference on Artificial Intelligence, p.870-878

Qingdong He||Zhengning Wang||Hao Zeng||Yi Zeng||Yijun Liu, "SVGA-Net: Sparse Voxel-Graph Attention Network for 3D Object Detection from Point Clouds", AAAI, p.870-878, 2022.

Qingdong He||Zhengning Wang||Hao Zeng||Yi Zeng||Yijun Liu. "SVGA-Net: Sparse Voxel-Graph Attention Network for 3D Object Detection from Point Clouds". Proceedings of the AAAI Conference on Artificial Intelligence, 2022, p.870-878.

Qingdong He||Zhengning Wang||Hao Zeng||Yi Zeng||Yijun Liu. "SVGA-Net: Sparse Voxel-Graph Attention Network for 3D Object Detection from Point Clouds". Proceedings of the AAAI Conference on Artificial Intelligence, (2022): 870-878.

Qingdong He||Zhengning Wang||Hao Zeng||Yi Zeng||Yijun Liu. SVGA-Net: Sparse Voxel-Graph Attention Network for 3D Object Detection from Point Clouds. AAAI[Internet]. 2022[cited 2023]; 870-878.


ISSN: 2374-3468


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