most citedContrastAlign: Toward Robust BEV Feature Alignment via Contrastive Learning for Multi-Modal 3D Object Detection

7 citations · 7 across the 2 of their papers we have counts for

collaborators

2 papers

cs.CV2024

MOS: Model Synergy for Test-Time Adaptation on LiDAR-Based 3D Object Detection

Zhuoxiao Chen, Junjie Meng, Mahsa Baktashmotlagh +3

LiDAR-based 3D object detection is crucial for various applications but often experiences performance degradation in real-world deployments due to domain shifts. While most studies…

cs.CV2024★ 7 cited

ContrastAlign: Toward Robust BEV Feature Alignment via Contrastive Learning for Multi-Modal 3D Object Detection

Ziying Song, Hongyu Pan, Feiyang Jia +8

In the field of 3D object detection tasks, fusing heterogeneous features from LiDAR and camera sensors into a unified Bird's Eye View (BEV) representation is a widely adopted parad…