FashionIQ

FashionIQ is a dataset used to evaluate composed image retrieval tasks by providing a collection of images paired with descriptive captions that specify modifications to the reference images.

Papers using FashionIQ (10)

ConeSep: Cone-based Robust Noise-Unlearning Compositional Network for Composed Image Retrieval2026 · 1 citesDAFM: Dynamic Adaptive Fusion for Multi-Model Collaboration in Composed Image Retrieval2025Pic2Word: Mapping Pictures to Words for Zero-shot Composed Image Retrieval2023 · 2 citesKnowledge-Enhanced Dual-stream Zero-shot Composed Image Retrieval2024 · 2 citesiSEARLE: Improving Textual Inversion for Zero-Shot Composed Image Retrieval2024 · 2 citesComposed Image Retrieval using Contrastive Learning and Task-oriented CLIP-based Features2023 · 1 citesLanguage-only Efficient Training of Zero-shot Composed Image Retrieval2023 · 1 citesImproving Composed Image Retrieval via Contrastive Learning with Scaling Positives and Negatives2024 · 1 citesImagine and Seek: Improving Composed Image Retrieval with an Imagined Proxy2024 · 1 citesTraining-free Zero-shot Composed Image Retrieval via Weighted Modality Fusion and Similarity2024