Skip to content

Code for NeurIPS 2019 paper Emergence of Object Segmentation in Perturbed Generative Models

Notifications You must be signed in to change notification settings

adambielski/perturbed-seg

Repository files navigation

Emergence of Object Segmentation in Perturbed Generative Models

Code for NeurIPS 2019 paper Emergence of Object Segmentation in Perturbed Generative Models.

Architecture

Samples

Usage

Tested with PyTorch version 1.2.0.

Download LSUN object dataset.

Sample train command for the layered generative model:

python train.py --max_size 128 --location_jitter 0.125 --min_mask_coverage 0.25 --mask_alpha 2.0 --mixing -d lsun /path/to/lmdb/ --bg_contrast_jitter 0.3 --org_to_crop 1.125 --sched

Credits

StyleGAN implementation used in this repository is based on this PyTorch port by rosinality.

About

Code for NeurIPS 2019 paper Emergence of Object Segmentation in Perturbed Generative Models

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages