Research map / Detection and segmentation / 3D detection and driving
Robust Multimodal Vehicle Detection in Foggy Weather Using Complementary Lidar and Radar Signals
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Fuse lidar and radar using MVDNet's two-stage late-fusion design | Vehicle detection on ORR · Clear+Foggy train; Foggy test | AP@IoU 0.5: 72.80 -> 87.40 | Helped |
| Train with fog-augmented as well as clear data | MVDNet · ORR Foggy test | AP@IoU 0.5: 77.98 -> 87.40 | Helped |
| Add explicit radar-lidar data synchronization (ablation) | MVDNet · ORR, clear and foggy test sets averaged | AP@IoU 0.5: 85.05 -> 89.15 | Helped |
| Add temporal fusion (ablation) | MVDNet · ORR, clear and foggy test sets averaged | AP@IoU 0.5: 88.19 -> 89.15 | Helped |
| Add sensor fusion (ablation) | MVDNet · ORR, clear and foggy test sets averaged | AP@IoU 0.5: 87.89 -> 89.15 | Helped |
| Add self attention (ablation) | MVDNet sensor fusion · ORR, clear and foggy test sets averaged | AP@IoU 0.5: 88.19 -> 89.15 | Helped |
| Add cross attention (ablation) | MVDNet sensor fusion · ORR, clear and foggy test sets averaged | AP@IoU 0.5: 88.31 -> 89.15 | Helped |
| Use both lidar and radar rather than radar alone (ablation) | MVDNet · ORR, clear and foggy test sets averaged | AP@IoU 0.5: 73.04 -> 89.15 | Helped |
| Use both lidar and radar rather than lidar alone (ablation) | MVDNet · ORR, clear and foggy test sets averaged | AP@IoU 0.5: 82.28 -> 89.15 | Helped |
| Fuse modalities late rather than reconstruct lidar through early fusion (ablation) | MVDNet · ORR, clear and foggy test sets averaged | AP@IoU 0.5: 85.04 -> 89.15 | Helped |
| Reduce region-fusion network size by 8× (ablation) | MVDNet-Fast · ORR, Clear+Foggy train; Foggy test | AP@IoU 0.5: 87.40 -> 85.58 | Hurt |
Closest papers by meaning
- L4DR: LiDAR-4DRadar Fusion for Weather-Robust 3D Object Detection (AAAI 2025 · similarity 0.88)
- Towards Robust 3D Object Detection with LiDAR and 4D Radar Fusion in Various Weather Conditions (CVPR 2024 · similarity 0.87)
- Equirectangular Point Reconstruction for Domain Adaptive Multimodal 3D Object Detection in Adverse Weather Conditions (AAAI 2025 · similarity 0.86)
- Sunshine to Rainstorm: Cross-Weather Knowledge Distillation for Robust 3D Object Detection (AAAI 2024 · similarity 0.86)
- V2X-Radar: A Multi-modal Dataset with 4D Radar for Cooperative Perception (NeurIPS 2025 · similarity 0.85)
- Resilient Sensor Fusion Under Adverse Sensor Failures via Multi-Modal Expert Fusion (CVPR 2025 · similarity 0.84)
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