Table Of Contents
Table Of Contents

Segmentation

Hint

The model names contain the training information. For instance, fcn_resnet50_voc:

  • fcn indicate the algorithm is “Fully Convolutional Network for Semantic Segmentation” [2].
  • resnet50 is the name of backbone network.
  • voc is the training dataset.

Semantic Segmentation

Table of pre-trained models for semantic segmentation and their performance.

Hint

The test script Download test.py can be used for evaluating the models (VOC results are evaluated using the official server). For example fcn_resnet50_ade:

python test.py --dataset ade20k --model-zoo fcn_resnet50_ade --eval

The training commands work with the script: Download train.py

Name Method pixAcc mIoU Command log
fcn_resnet101_coco FCN [2] 92.2 66.2 shell script log
psp_resnet101_coco PSP [3] 92.4 70.4 shell script log
deeplab_resnet101_coco DeepLabV3 [4] 92.5 70.4 shell script log
fcn_resnet101_voc FCN [2] N/A 83.6 shell script log
psp_resnet101_voc PSP [3] N/A 85.1 shell script log
deeplab_resnet101_voc DeepLabV3 [4] N/A 86.2 shell script log
deeplab_resnet152_voc DeepLabV3 [4] N/A 86.7 shell script log
fcn_resnet50_ade FCN [2] 79.0 39.5 shell script log
fcn_resnet101_ade FCN [2] 80.6 41.6 shell script log
psp_resnet50_ade PSP [3] 80.1 41.6 shell script log
psp_resnet101_ade PSP [3] 80.8 42.9 shell script log
deeplab_resnet50_ade DeepLabV3 [4] 80.5 42.5 shell script log
deeplab_resnet101_ade DeepLabV3 [4] 81.1 44.1 shell script log
psp_resnet101_citys PSP [3] N/A 77.1 shell script log

Instance Segmentation

Table of pre-trained models for instance segmentation and their performance.

Hint

The training commands work with the following scripts:

For COCO dataset, training imageset is train2017 and validation imageset is val2017.

Average precision with IoU threshold 0.5:0.95 (averaged 10 values), 0.5 and 0.75 are reported together in the format (AP 0.5:0.95)/(AP 0.5)/(AP 0.75).

For instance segmentation task, both box overlap and segmentation overlap based AP are evaluated and reported.

Model Box AP Segm AP Command Training Log
mask_rcnn_resnet50_v1b_coco 38.3/58.7/41.4 33.1/54.8/35.0 shell script log
[1]He, Kaming, Georgia Gkioxari, Piotr Dollár and Ross Girshick. “Mask R-CNN.” In IEEE International Conference on Computer Vision (ICCV), 2017.
[2](1, 2, 3, 4, 5) Long, Jonathan, Evan Shelhamer, and Trevor Darrell. “Fully convolutional networks for semantic segmentation.” Proceedings of the IEEE conference on computer vision and pattern recognition. 2015.
[3](1, 2, 3, 4, 5) Zhao, Hengshuang, Jianping Shi, Xiaojuan Qi, Xiaogang Wang, and Jiaya Jia. “Pyramid scene parsing network.” CVPR, 2017
[4](1, 2, 3, 4, 5) Chen, Liang-Chieh, et al. “Rethinking atrous convolution for semantic image segmentation.” arXiv preprint arXiv:1706.05587 (2017).