mlsanityData to 14 Oct 2026

Revisiting Radar Camera Alignment by Contrastive Learning for 3D Object Detection

arXiv 2504.16368 ↗First posted 23 Apr 2025cs.CVcited by 0

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Abstract (arXiv)

Recently, 3D object detection algorithms based on radar and camera fusion have shown excellent performance, setting the stage for their application in autonomous driving perception tasks. Existing methods have focused on dealing with feature misalignment caused by the domain gap between radar and camera. However, existing methods either neglect inter-modal features interaction during alignment or fail to effectively align features at the same spatial location across modalities. To alleviate the above problems, we propose a new alignment model called Radar Camera Alignment (RCAlign). Specifically, we design a Dual-Route Alignment (DRA) module based on contrastive learning to align and fuse the features between radar and camera. Moreover, considering the sparsity of radar BEV features, a Radar Feature Enhancement (RFE) module is proposed to improve the densification of radar BEV features with the knowledge distillation loss. Experiments show RCAlign achieves a new state-of-the-art on the public nuScenes benchmark in radar camera fusion for 3D Object Detection. Furthermore, the RCAlign achieves a significant performance gain (4.3% NDS and 8.4% mAP) in real-time 3D detection compared to the latest state-of-the-art method (RCBEVDet).

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 61 of its 82 references that are in the map. First posted on arXiv 23 Apr 2025.

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61 of 82 references.

References · 61

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38 more
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  1. 2025RCTDistill: Cross-Modal Knowledge Distillation Framework for Radar-Camera 3D Object Detection with Temporal Fusion
  2. 2025IMKD: Intensity-Aware Multi-Level Knowledge Distillation for Camera-Radar Fusion
  3. 2024A Survey of Deep Learning Based Radar and Vision Fusion for 3D Object Detection in Autonomous Driving
  4. 2025M^3Detection: Multi-Frame Multi-Level Feature Fusion for Multi-Modal 3D Object Detection with Camera and 4D Imaging Radar
  5. 2024CRKD: Enhanced Camera-Radar Object Detection with Cross-modality Knowledge Distillation
  6. 2025Improving Generalization Ability for 3D Object Detection by Learning Sparsity-invariant Features
  7. 2025SpaRC-AD: A Baseline for Radar-Camera Fusion in End-to-End Autonomous Driving
  8. 2026Stereo 4D Radar for 3D Object Detection: Integrating Geometric Alignment and Absolute Velocity Estimation