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Self-attention on Multi-shifted Windows for Scene Segmentation

Introduction

This is the PyTorch implementation of our [Self-attention on Multi-shifted Windows for Scene Segmentation] by Litao Yu, Zhibin Li and Jian Zhang

Use of code

This implementation is built based on mmsegmentation (https://mmsegmentation.readthedocs.io/). Please follow their instructions to install the necessary modules for running the programs.

Results and models

Pascal VOC 2012 + Aug

Method Backbone Crop Size Lr schd mIoU mIoU(ms+flip) config download
MSwin-P Swin-S 512x512 80000 81.58 82.95 config model
MSwin-S Swin-S 512x512 80000 81.97 82.74 config model
MSwin-C Swin-S 512x512 80000 81.40 82.70 config model
MSwin-P Swin-B 512x512 80000 82.85 83.82 config model
MSwin-S Swin-B 512x512 80000 82.86 84.27 config model
MSwin-C Swin-B 512x512 80000 83.50 84.47 config model

Pascal COCOStuff-10K

Method Backbone Crop Size Lr schd mIoU mIoU(ms+flip) config download
MSwin-P Swin-S 480x480 40000 39.8 41.1 config model
MSwin-S Swin-S 480x480 40000 40.2 42.1 config model
MSwin-C Swin-S 480x480 40000 39.6 41.6 config model
MSwin-P Swin-B 480x480 40000 41.3 42.7 config model
MSwin-S Swin-B 480x480 40000 41.1 42.4 config model
MSwin-C Swin-B 480x480 40000 41.0 42.8 config model

ADE20K

Method Backbone Crop Size Lr schd mIoU mIoU(ms+flip) config download
MSwin-P Swin-S 512x512 160000 47.11 48.55 config model
MSwin-S Swin-S 512x512 160000 47.52 48.56 config model
MSwin-C Swin-S 512x512 160000 46.26 48.12 config model
MSwin-P Swin-B 512x512 160000 48.38 50.29 config model
MSwin-S Swin-B 512x512 160000 48.54 50.26 config model
MSwin-C Swin-B 512x512 160000 48.70 50.13 config model

Cityscapes

Method Backbone Crop Size Lr schd mIoU mIoU(ms+flip) config download
MSwin-P Swin-B 512x1024 80000 81.06 82.10 config model
MSwin-S Swin-B 512x1024 80000 80.87 82.39 config model
MSwin-C Swin-B 512x1024 80000 80.78 82.04 config model

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