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fmcarlucci
197 Stars 37 Forks GNU Affero General Public License v3.0 96 Commits 14 Opened issues

Description

Repository for the CVPR19 oral paper "Domain Generalization by Solving Jigsaw Puzzles"

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JIGEN

JigenDG

Repository for the CVPR19 oral paper "Domain Generalization by Solving Jigsaw Puzzles". To cite, please use:

@inproceedings{carlucci2019domain,
  title={Domain Generalization by Solving Jigsaw Puzzles},
  author={Carlucci, Fabio Maria and D'Innocente, Antonio and Bucci, Silvia and Caputo, Barbara and Tommasi, Tatiana},
  booktitle={CVPR},
  year={2019}
}

SETUP

Pytorch models will automatically download if needed. You can download the caffemodel we used for AlexNet from here https://drive.google.com/file/d/1wUJTH1Joq2KAgrUDeKJghP1Wf7Q9w4z-/view?usp=sharing

Once downloaded, move it into models/pretrained/alexnet_caffe.pth.tar

Once you have download the data for the different experiments, you must update the files in data/txtlist to match the actual location of your files. For example, if you saved your data into /home/user/data/images/ you have to change these lines: ``` /home/fmc/data/PACS/kfold/artpainting/dog/pic001.jpg 0 /home/fmc/data/PACS/kfold/artpainting/dog/pic002.jpg 0 /home/fmc/data/PACS/kfold/artpainting/dog/pic_003.jpg 0 ``` into:

/home/user/data/images/PACS/kfold/art_painting/dog/pic_001.jpg 0
/home/user/data/images/PACS/kfold/art_painting/dog/pic_002.jpg 0
/home/user/data/images/PACS/kfold/art_painting/dog/pic_003.jpg 0

A quick way is to use sed:

for i in *.txt; do sed -i "[email protected]/home/fmc/data/@/home/user/data/images/@g" $i; done

Running experiments

Run runPACSphoto.sh to run the DG experiment on PACS, with photo as target (using AlexNet).

Note that when using ResNet you should set the imagesize to 222 An example on how to get ResNet18 results on PACS, artpainting as target:

python train_jigsaw.py --batch_size 128 --n_classes 7 --learning_rate 0.001 --network resnet18 --val_size 0.1 --folder_name test --jigsaw_n_classes 30 --train_all True --TTA False --nesterov False --min_scale 0.8 --max_scale 1.0 --random_horiz_flip 0.5 --jitter 0.4 --tile_random_grayscale 0.1 --source photo cartoon sketch --target art_painting --jig_weight 0.7 --bias_whole_image 0.9 --image_size 222

VLCS

Some people are having issues accessing the VLCS dataset; I have uploaded a copy here: http://www.mediafire.com/file/7yv132lgn1v267r/vlcs.tar.gz/file

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