README.md

Common settings

• All baselines were trained using 8 GPU with a batch size of 8 (1 images per GPU) using the linear scaling rule to scale the learning rate.
• All models were trained on cityscapes_train, and tested on cityscapes_val.
• 1x training schedule indicates 64 epochs which corresponds to slightly less than the 24k iterations reported in the original schedule from the Mask R-CNN paper
• All pytorch-style pretrained backbones on ImageNet are from PyTorch model zoo.

Baselines

Download links and more models with different backbones and training schemes will be added to the model zoo.

Faster R-CNN

Backbone	Style	Lr schd	Scale	Mem (GB)	Train time (s/iter)	Inf time (fps)	box AP	Download
R-50-FPN	pytorch	1x	800-1024	4.9	0.345	8.8	36.0	model

Mask R-CNN

Backbone	Style	Lr schd	Scale	Mem (GB)	Train time (s/iter)	Inf time (fps)	box AP	mask AP	Download
R-50-FPN	pytorch	1x	800-1024	4.9	0.609	2.5	37.4	32.5	model

Notes:

• In the original paper, the mask AP of Mask R-CNN R-50-FPN is 31.5.