GitHub

xMOD: Cross-Modal Distillation for 2D/3D Multi-Object Discovery from 2D motion

Object discovery, which refers to the task of localizing objects without human annotations, has gained significant attention in 2D image analysis. However, despite this growing interest, it remains ...
IEEE

Semantic-aware Fine-grained Point Augmentation for 3D Multi-modal Object Detection

3D object detection aims to locate and recognize the object from the point cloud, which is a meaningful and foundation task in autonomous driving. However, the sparsity of the point cloud poses a ...
GitHub

State Space Model Meets Transformer: A New Paradigm for 3D Object Detection

DETR-based methods, which use multi-layer transformer decoders to refine object queries iteratively, have shown promising performance in 3D indoor object detection. However, the scene point features ...
IEEE

Cooperative 3D Multi-Object Tracking With Cross-Agent Data Association for Connected and Automated Vehicles

Abstract: Achieving reliable 3D multi-object tracking (MOT) is essential for enabling autonomous driving. With the aid of communication techniques, vehicles could share complementary environmental ...