Adversarial Semantic Hallucination for Domain Generalized Semantic Segmentation

This is a pytorch implementation of [ASH]().

Prerequisites

• Python 3.6
• GPU Memory >= 16G
• Pytorch 1.6.0

Getting started

• Download The GTA5 Dataset

• Download The SYNTHIA Dataset

• Download The Cityscapes Dataset

The data folder is structured as follows:

├── data/
│   ├── Cityscapes/     
|   |   ├── gtFine/
|   |   ├── leftImg8bit/
│   ├── GTA5/
|   |   ├── images/
|   |   ├── labels/
│   ├── SYNTHIA/ 
|   |   ├── RAND_CITYSCAPES/
│   └──             
└── model/
│   ├── DeepLab_resnet_pretrained.pth
...

Train

CUDA_VISIBLE_DEVICES=0 python train.py --snapshot-dir ./snapshots/GTA2Cityscapes

This code is heavily borrowed from the baseline CLAN https://github.com/RoyalVane/CLAN ) and pytorch_adain (https://github.com/naoto0804/pytorch-AdaIN)

GTA trained model https://drive.google.com/file/d/1eVnDMC3ytyl5Wx8H5VPKoTNq1UGXmS56/view?usp=sharing

SYN trained model https://drive.google.com/file/d/1XTmJhXCGeD2KrK7M7Xklq0Gayvd0n86e/view?usp=sharing

Citation

If you use this code in your research please consider citing

@inproceedings{ASH,
  author    = {Gabriel Tjio and
               Ping Liu and
               Joey Tianyi Zhou and
               Rick Siow Mong Goh},
  title     = {Adversarial Semantic Hallucination for Domain Generalized Semantic
               Segmentation},
 booktitle = {IEEE Winter Conf. on Applications of Computer Vision},
 year = {2022}
}