| Polyvore Outfits version 1.0 | |
| This dataset consists of 68,306 outfits and their meta data crawled from the | |
| polyvore website. We do not own the copyright of the images or meta-data | |
| provided, and are solely provided for research and educational purposes. If | |
| you use our data, please consider citing our paper: | |
| @inproceedings{VasilevaECCV18FasionCompatibility, | |
| Author = {Mariya I. Vasileva and Bryan A. Plummer and Krishna Dusad and | |
| Shreya Rajpal and Ranjitha Kumar and David Forsyth}, | |
| Title = {Learning Type-Aware Embeddings for Fashion Compatibility}, | |
| booktitle = {ECCV}, | |
| Year = {2018} | |
| } | |
| ## Dataset Splits | |
| In our paper we describe two versions of the data: | |
| Polyvore Outfits (nondisjoint) - Outfits are split at random, which means some | |
| items (but not complete outfits) may be seen in both training and test splits. | |
| Polyvore Outfits (disjoint) - Outfits in the test/validation set do not share | |
| any items in common with outfits in the training set (although some items in | |
| the test set may be present in outfits in the validation set) | |
| Within each version folder we have: | |
| <test/valid/train>.json - a list of outfits, their item_id's, and their | |
| ordering (index) we imposed when we compared to prior work using an LSTM | |
| typespaces.p - a list of tuples (t1, t2), each of which identifies a type- | |
| specific embedding that compares items of type t1 to items of type t2 | |
| train_hglmm_pca6000.txt - each row contains 6001 comma separated values, where | |
| the first element is the label, and the remaining 6000 dimensions are the | |
| PCA-reduced HGLMM fisher vectors (note: the "label" may also contain a comma) | |
| The remaining files in these folders are for the tasks used to evaluate our | |
| models. They contain item identifiers of the form <set_id>_<index>, which can | |
| be mapped back to item_id's using the list of outfits mentioned above. These | |
| remaining files are: | |
| compatibility_<test/valid/train>.txt - fashion compatibility experiment data, | |
| where each row is an outfit sample. The first element of the outfit sample is | |
| the label (1/0 for positive/negative) and the remaining elements are item | |
| identifiers in that sample. | |
| fill_in_blank_<test/valid/train>.json - fill-in-the-blank experiment data, | |
| contains an array of dictionaries. These dictionaries contain the question/ | |
| answer pairs, and also identifies the "index" of the item in the outfit in | |
| "blank_position". Since the set_id is used in the item identifiers, the | |
| correct answer can be determined by matching the set_id in the question | |
| elements with the set_id in the answers. | |
| ## Maryland Polyvore Test Data | |
| We provide the fashion compatibility and fill-in-the-blank test data we used in | |
| our paper. This data is more difficult than those used in the original paper | |
| because they replace items of the same type when creating negatives rather than | |
| those sampled at random provided with the Maryland Polyvore dataset. See our | |
| paper for more details. | |
| ## Images and Meta-Data | |
| Images are stored by their item_id, which are organized in lists of outfits for | |
| each each version of the dataset. | |
| polyvore_item_metadata.json - contains a dictionary where each key is an | |
| item_id, and the values are its associated meta-data labels. | |
| polyvore_outfit_titles.json - contains a dictionary where each key is a set_id | |
| and the values are its associated meta-data labels. | |
| categories.csv - Each row contains three items: (category_id, fine-grained | |
| category, semantic category) |