191 citations · 198 across the 5 of their papers we have counts for
5 papers
You Only Look Bottom-Up for Monocular 3D Object Detection
Kaixin Xiong, Dingyuan Zhang, Dingkang Liang +5
Monocular 3D Object Detection is an essential task for autonomous driving. Meanwhile, accurate 3D object detection from pure images is very challenging due to the loss of depth inf…
Diffusion-based 3D Object Detection with Random Boxes
Xin Zhou, Jinghua Hou, Tingting Yao +6
3D object detection is an essential task for achieving autonomous driving. Existing anchor-based detection methods rely on empirical heuristics setting of anchors, which makes the…
Multi-Modal 3D Object Detection by Box Matching
Zhe Liu, Xiaoqing Ye, Zhikang Zou +5
Multi-modal 3D object detection has received growing attention as the information from different sensors like LiDAR and cameras are complementary. Most fusion methods for 3D detect…
StereoDistill: Pick the Cream from LiDAR for Distilling Stereo-based 3D Object Detection
Zhe Liu, Xiaoqing Ye, Xiao Tan +2
In this paper, we propose a cross-modal distillation method named StereoDistill to narrow the gap between the stereo and LiDAR-based approaches via distilling the stereo detectors…
PRA-Net: Point Relation-Aware Network for 3D Point Cloud Analysis
Silin Cheng, Xiwu Chen, Xinwei He +2
Learning intra-region contexts and inter-region relations are two effective strategies to strengthen feature representations for point cloud analysis. However, unifying the two str…