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20192024
most citedTransformation-Equivariant 3D Object Detection for Autonomous Driving

13 citations · 29 across the 4 of their papers we have counts for

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7 papers · 1 filter

cs.CV2024

SC3D: Label-Efficient Outdoor 3D Object Detection via Single Click Annotation

Qiming Xia, Hongwei Lin, Wei Ye +4

LiDAR-based outdoor 3D object detection has received widespread attention. However, training 3D detectors from the LiDAR point cloud typically relies on expensive bounding box anno…

cs.CV2024

Commonsense Prototype for Outdoor Unsupervised 3D Object Detection

Hai Wu, Shijia Zhao, Xun Huang +3

The prevalent approaches of unsupervised 3D object detection follow cluster-based pseudo-label generation and iterative self-training processes. However, the challenge arises due t…

cs.CV20242 cited

Sunshine to Rainstorm: Cross-Weather Knowledge Distillation for Robust 3D Object Detection

Xun Huang, Hai Wu, Xin Li +3

LiDAR-based 3D object detection models have traditionally struggled under rainy conditions due to the degraded and noisy scanning signals. Previous research has attempted to addres…

cs.CV202213 cited

Transformation-Equivariant 3D Object Detection for Autonomous Driving

Hai Wu, Chenglu Wen, Wei Li +3

3D object detection received increasing attention in autonomous driving recently. Objects in 3D scenes are distributed with diverse orientations. Ordinary detectors do not explicit…

cs.CV20198 cited

Point2Node: Correlation Learning of Dynamic-Node for Point Cloud Feature Modeling

Wenkai Han, Chenglu Wen, Cheng Wang +2

Fully exploring correlation among points in point clouds is essential for their feature modeling. This paper presents a novel end-to-end graph model, named Point2Node, to represent…

cs.CV20196 cited

RF-Net: An End-to-End Image Matching Network based on Receptive Field

Xuelun Shen, Cheng Wang, Xin Li +5

This paper proposes a new end-to-end trainable matching network based on receptive field, RF-Net, to compute sparse correspondence between images. Building end-to-end trainable mat…