This repository hosts the dataset and source code for the paper "A causal view of compositional zero-shot recognition". Yuval Atzmon, Felix Kreuk, Uri Shalit, Gal Chechik, NeurIPS 2020 (Spotlight)
AO-CLEVr is a new synthetic-images dataset containing images of "easy" Attribute-Object categories, based on the CLEVr framework (Johnson et al. CVPR 2017). AO-CLEVr has attribute-object pairs created from 8 attributes: { red, purple, yellow, blue, green, cyan, gray, brown } and 3 object shapes {sphere, cube, cylinder}, yielding 24 attribute-object pairs. Each pair consists of 7500 images. Each image has a single object that consists of the attribute-object pair. The object is randomly assigned one of two sizes (small/large), one of two materials (rubber/metallic), a random position, and random lightning according to CLEVr defaults.
The dataset can be downloaded from the following url.
(Under construction)
If you use the contents of this project, please cite our paper.
@inproceedings{neurips2020_causal_comp_atzmon, author = {Atzmon, Yuval and Kreuk, Felix and Shalit, Uri and Chechik, Gal}, booktitle = {Advances in Neural Information Processing Systems (NeurIPS)}, title = {A causal view of compositional zero-shot recognition}, year = {2020} }