Detection Models



Network
box AP
mask AP
keypoint AP




Faster R-CNN ResNet-50 FPN trained on COCO
37.0
 
 


Mask R-CNN ResNet-50 FPN trained on COCO
37.9
34.6
 


Keypoint R-CNN ResNet-50 FPN trained on COCO
54.6
 
65.0



The implementations of the models for object detection, instance segmentation and keypoint detection are fast, specially during training.
In the following table, we use 8 V100 GPUs, with CUDA 10.0 and CUDNN 7.4 to report the results. During training, we use a batch size of 2 per GPU, and during testing a batch size of 1 is used.
For test time, we report the time for the model evaluation and post-processing (including mask pasting in image), but not the time for computing the precision-recall.



Network
train time (s / it)
test time (s / it)
memory (GB)




Faster R-CNN ResNet-50 FPN
0.2288
0.0590
5.2


Mask R-CNN ResNet-50 FPN
0.2728
0.0903
5.4


Keypoint R-CNN ResNet-50 FPN
0.3789
0.1242
6.8


