Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

Benchmark Model Rank Results
vessel-detection-on-vessel-detection-datesetFaster RCNN#1AP: 64.3%
object-detection-on-ua-detracFaster R-CNN#7mAP: 58.45
2d-object-detection-on-sardet-100kF-RCNN#9box mAP: 49.0
object-counting-on-carpkFaster R-CNN (2015)#10MAE: 39.88RMSE: 47.67
robust-object-detection-on-cityscapesBaseline#15mPC [AP]: 15.4
object-detection-on-pascal-voc-2007Faster R-CNN#23MAP: 73.2%
object-detection-on-coco-oFaster R-CNN (ResNet-50-FPN)#40Average mAP: 16.4Effective Robustness: -0.41
object-detection-on-coco-test-devFaster R-CNN (VGG-16)#193box mAP: 21.9