FashionRec: 331k Multimodal Outfit Samples for Fashion Recommendation

FashionRec is a multimodal dataset with 331,124 samples designed to train Vision-Language Models for fashion recommendation. It was created by Anony100 and last updated on October 14, 2025. The dataset integrates human-curated outfits with dialogue data sourced from three fashion datasets: iFashion, Polyvore-519, and Fashion32.

Use Cases

• Train models for basic fashion item recommendation based on multimodal outfit data.
• Develop personalized recommendation systems based on integrated dialogue data.
• Build models for suggesting alternative fashion items based on outfit context.
• Benchmark multimodal models on tasks combining visual outfit data and textual dialogue.

Strengths

• Contains 331,124 samples, providing a substantial scale for model training.
• Integrates three distinct data sources (iFashion, Polyvore-519, Fashion32) for diversity.
• Explicitly designed for three key recommendation types: Basic, Personalized, and Alternative.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is known, but specific file formats, size, and license details are unknown.
• Data may reflect the geographic, temporal, or stylistic biases inherent to its three source datasets.

Provenance

Source

An aggregation of three fashion datasets: iFashion, Polyvore-519, and Fashion32.

Collection Method

Human-curated outfits integrated with dialogue data.

Time Range

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Freshness

Last updated 2025-10-14 10:14:37; freshness should be verified.

Geography

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