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Found 5 papers, 4 papers with code
HandsOff: Labeled Dataset Generation With No Additional Human Annotations
Recent work leverages the expressive power of generative adversarial networks (GANs) to generate labeled synthetic datasets.
OutfitTransformer: Learning Outfit Representations for Fashion Recommendation
For compatibility prediction, we design an outfit token to capture a global outfit representation and train the framework using a classification loss.
Learning Similarity Conditions Without Explicit Supervision
Many real-world tasks require models to compare images along multiple similarity conditions (e. g. similarity in color, category or shape).
Why do These Match? Explaining the Behavior of Image Similarity Models
Explaining a deep learning model can help users understand its behavior and allow researchers to discern its shortcomings.
Learning Type-Aware Embeddings for Fashion Compatibility
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.
