Search Results for author:
Found 5 papers, 4 papers with code
SparseAD: Sparse Query-Centric Paradigm for Efficient End-to-End Autonomous Driving
End-to-End paradigms use a unified framework to implement multi-tasks in an autonomous driving system.
EPNet++: Cascade Bi-directional Fusion for Multi-Modal 3D Object Detection
Recently, fusing the LiDAR point cloud and camera image to improve the performance and robustness of 3D object detection has received more and more attention, as these two modalities naturally possess strong complementarity.
PRA-Net: Point Relation-Aware Network for 3D Point Cloud Analysis
Learning intra-region contexts and inter-region relations are two effective strategies to strengthen feature representations for point cloud analysis.
Ranked #39 on
3D Point Cloud Classification
on ModelNet40
TransCrowd: weakly-supervised crowd counting with transformers
Current weakly-supervised counting methods adopt the CNN to regress a total count of the crowd by an image-to-count paradigm.
EPNet: Enhancing Point Features with Image Semantics for 3D Object Detection
In this paper, we aim at addressing two critical issues in the 3D detection task, including the exploitation of multiple sensors~(namely LiDAR point cloud and camera image), as well as the inconsistency between the localization and classification confidence.
