2D Object Detection On Dronevehicle
Metrics
Val/mAP50
test/mAP
test/mAP50
Results
Performance results of various models on this benchmark
Model Name | Val/mAP50 | test/mAP | test/mAP50 | Paper Title | Repository |
|---|---|---|---|---|---|
| C2Former | 74.2 | 42.8 | 72.8 | $mathbf{C}^2$Former: Calibrated and Complementary Transformer for RGB-Infrared Object Detection | |
| AR-CNN | 71.6 | - | - | Weakly Aligned Cross-Modal Learning for Multispectral Pedestrian Detection | - |
| TSFADet | 73.1 | - | 70.4 | Translation, Scale and Rotation: Cross-Modal Alignment Meets RGB-Infrared Vehicle Detection | - |
| UA-CMDet | - | 40.1 | 64.0 | Drone-based RGB-Infrared Cross-Modality Vehicle Detection via Uncertainty-Aware Learning | |
| TarDAL | - | 43.3 | 72.6 | Target-aware Dual Adversarial Learning and a Multi-scenario Multi-Modality Benchmark to Fuse Infrared and Visible for Object Detection | |
| CIAN | 70.2 | - | - | CIAN: Cross-Image Affinity Net for Weakly Supervised Semantic Segmentation | |
| CALNet | 76.4 | - | 75.4 | - | - |
| GLFNet | - | 42.9 | 71.4 | - | - |
| CAGTDet | 74.6 | - | - | - | - |
| HalfwayFusion | 68.2 | - | - | Multispectral Deep Neural Networks for Pedestrian Detection | |
| OAFA | - | - | 79.4 | Weakly Misalignment-free Adaptive Feature Alignment for UAVs-based Multimodal Object Detection | - |
0 of 11 row(s) selected.