2793145003 / ReDO

Code for paper Unsupervised Object Segmentation by Redrawing

ReDO

Code for paper Unsupervised Object Segmentation by Redrawing.

Datasets

Flowers:

1. Download and extract: Dataset, Segmentations, and data splits from http://www.robots.ox.ac.uk/~vgg/data/flowers/102/
2. The obtained jpg folder, segmin folder and setid.mat file should be placed in the same data root folder.

CUB:

1. Download and extract Images and Segmentations from http://www.vision.caltech.edu/visipedia/CUB-200-2011.html
2. Place the segmentations folder in the CUB_200_2011 folder.
3. Place the train_val_test_split.txt file from this repo in the CUB_200_2011 folder.
4. dataroot should be set to the CUB_200_2011 folder.

LFW:

1. Download and extract the funneled images from http://vis-www.cs.umass.edu/lfw/
2. Download and extract the ground truth images from http://vis-www.cs.umass.edu/lfw/part_labels/
3. Place the obtained lfw_funneled and parts_lfw_funneled_gt_images folders in the same data root folder.
4. Also place the train.txt, val.txt and test.txt files from the repo in this data root folder.

Example usage

Tested on python3.7 with pytorch 1.0.1

python redo.py --dataset flowers --nfX 32 --useSelfAttG --useSelfAttD --outf path_to_output_folder --dataroot path_to_data_folder

Random samples (from paper)

Those are not cherry-picked.

Column 1: Input

Column 2: Ground Truth

Column 3: output mask for object 1

Columns 4-7: generated image with redrawn object 1

Columns 8-11: generated image with redrawn object 2