Exploiting-Temporality-For-Semi-Supervised-Video-Segmentation

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Exploiting-Temporality-For-Semi-Supervised-Video-Segmentation

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Code for the paper "Exploiting Temporality for Semi Supervised Video Segmentation" (ICCV '19)

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# Exploiting Temporality For Semi Supervised Video Segmentation 
This repository contains the corresponding training for [**the paper**](http://openaccess.thecvf.com/content_ICCVW_2019/papers/CVRSUAD/Sibechi_Exploiting_Temporality_for_Semi-Supervised_Video_Segmentation_ICCVW_2019_paper.pdf).

## Training on Cityscapes
1. Set the root of your cityscapes folder in the [cityscapes dataloader](dataloader/cityscapes.py). For training the sequence models, you need to ask permission for the sequence version of the cityscapes dataset from https://www.cityscapes-dataset.com/.
2. Check the [available parser options](parser_options.py).
4. Train the networks using the provided training scripts ([1](train_cityscapes.sh), [2](big_train_cityscapes.sh)):
- Frame-by-Frame:
`bash train_cityscapes.sh unet fbf 512,256 4 amsgrad 0.0001 0 1 8 128`
- Modelling temporality at the bottleneck:
`bash train_cityscapes.sh unet sequence-1234 512,256 4 amsgrad 0.0001 0 2 8 128 0 convlstm`
- Modelling temporality at every skip connection level:
`bash train_cityscapes.sh unet sequence-1234 512,256 4 amsgrad 0.0001 0 2 8 128 0 convlstm+temporal_skip`
- Modelling temporality in the encoder:
`bash big_train_cityscapes.sh unet sequence-1234 512,256 4 amsgrad 0.0001 0 2 8 128 0 convlstm+temporal_encoder`
5. If you want to use a different temporal module, replace `convlstm` with `tcn` (Pointwise TCN), `tcn2d` or `tcn2dhw`. More details [here](parser_options.py)

## Results

### Effect of temporal module locations

### Effect of temporal module types

 <img src="how-to-model.png">

## Citation:
If you use this code, please consider citing our work-
```
@inproceedings{Sibechi_2019_ICCV,
author = {Sibechi, Radu and Booij, Olaf and Baka, Nora and Bloem, Peter},
title = {Exploiting Temporality for Semi-Supervised Video Segmentation},
booktitle = {The IEEE International Conference on Computer Vision (ICCV) Workshops},
month = {Oct},
year = {2019}
} 
```

Exploiting-Temporality-For-Semi-Supervised-Video-Segmentation

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