PolyvoreOutfitDataset

Polyvore Dataset is widely used for learning fashion compatibility. There are several different split versions of this dataset. We deployed Learning Type Aware Embeddings for Fashion Compatibility here.

• Polyvore Outfits(Nondisjoint)

  Outfits are split at random. The training dataset and testing dataset may have overlapped items(garments).

• Polyvore Outfits(Disjoint)

  The training set and testing/validation set have no overlapped items.

Annotations

• train/test/valid.json

  A list of outfits, their item_id and their ordering(index).

• 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, the remaining 6000 dimensions are the PCA-reduced HGLMM fisher vectors (note: the "label" may also contain a comma).

• compatibility_train/test/valid.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_train/test/valid.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.

Images

Images are stored by their item_id, which are organized in lists of outfits for each each version of the dataset.

Meta-Data

• polyvore_item_metadata.json

  It contains a dictionary where each key is an item_id, and the values are its associated meta-data labels.

• polyvore_outfit_titles.json

  It 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 categroy.