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Code for Universal Semi-Supervised Semantic Segmentation models paper accepted in ICCV 2019
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README.md

USSS_ICCV19

Code for Universal Semi Supervised Semantic Segmentation accepted to ICCV 2019.
Full Paper available at https://arxiv.org/abs/1811.10323.

Requirements

Python >= 2.6
PyTorch >= 1.0.0
The ImageNet pretrained models are downloaded from the repository at https://github.com/fyu/drn.

Datasets

Cityscapes: https://www.cityscapes-dataset.com/
IDD: https://idd.insaan.iiit.ac.in/

How to run

python segment.py --basedir <basedir> --lr 0.001 --num-epochs 200 --batch-size 8 --savedir <savedir> --datasets <D1> [<D2> ..] --num-samples <N> --alpha 0 --beta 0 --resnet <resnet_v> --model drnet

Acknowledgements

Part of the code is heavily borrowed from the official code release of Dilated Residual Networks (https://github.com/fyu/drn) and IDD Dataset (https://github.com/AutoNUE/public-code).

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