25 citations · 46 across the 6 of their papers we have counts for
5 papers · 1 filter
HandsOff: Labeled Dataset Generation With No Additional Human Annotations
Austin Xu, Mariya I. Vasileva, Achal Dave +1
Recent work leverages the expressive power of generative adversarial networks (GANs) to generate labeled synthetic datasets. These dataset generation methods often require new anno…
OutfitTransformer: Learning Outfit Representations for Fashion Recommendation
Rohan Sarkar, Navaneeth Bodla, Mariya I. Vasileva +4
Learning an effective outfit-level representation is critical for predicting the compatibility of items in an outfit, and retrieving complementary items for a partial outfit. We pr…
Learning Similarity Conditions Without Explicit Supervision
Reuben Tan, Mariya I. Vasileva, Kate Saenko +1
Many real-world tasks require models to compare images along multiple similarity conditions (e.g. similarity in color, category or shape). Existing methods often reason about these…
Why do These Match? Explaining the Behavior of Image Similarity Models
Bryan A. Plummer, Mariya I. Vasileva, Vitali Petsiuk +2
Explaining a deep learning model can help users understand its behavior and allow researchers to discern its shortcomings. Recent work has primarily focused on explaining models fo…
Learning Type-Aware Embeddings for Fashion Compatibility
Mariya I. Vasileva, Bryan A. Plummer, Krishna Dusad +3
Outfits in online fashion data are composed of items of many different types (e.g. top, bottom, shoes) that share some stylistic relationship with one another. A representation for…