AR-CNN

Reported on 2 benchmarks across 2 tasks · 1 paper · 1 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Methodology1 result

2D Object DetectiononDroneVehicle
Val/mAP50· 2019-01-09
71.6
best: 76.4 (CALNet)
SOTA
Weakly Aligned Cross-Modal Learning for Multispectral Pedestrian Detection arXiv:1901.02645

Computer Vision1 result

Multispectral Object DetectiononKAIST Multispectral Pedestrian Detection Benchmark
All Miss Rate· 2019-01-09
34.95
best: 51.7 (FusionRPN+BF)
Weakly Aligned Cross-Modal Learning for Multispectral Pedestrian Detection arXiv:1901.02645