Code for the paper:

Borrowing from yourself: Faster future video segmentation with partial channel update

Install requirements

pip install -r requirements.txt

HOW TO TRAIN

1. Choose model and configuration from scripts folder
2. Add path to the root of the Cityscapes dataset in the json config file in variable db_root
3. Run training using the run.sh script with the folder name as first parameter and the config file name as second parameter

Examples:

./run.sh deeplab_base config_50.json

./run.sh swiftnet_base config.json

HOW TO EVALUTATE

1. Check model and configuration of trained model from scripts folder
2. Run evaluation using the run.sh script with the folder name as first parameter and the config file name as second parameter, and the path to the learned model as third parameter

Example:

./run.sh deeplab_base config_50.json runs/deeplab/dl_50_sgd/experiment_0/checkpoint.pth