DeepFashion Database

Categories: Research, Data Analysis | Pricing: Free | Official Website ↗

DeepFashion is a large-scale database of over 800,000 fashion images with rich annotations for computer vision research.

DeepFashion is a comprehensive database designed for visual fashion analysis, containing over 800,000 diverse fashion images. These images range from well-posed shop photos to unconstrained consumer pictures, making it a substantial resource for various computer vision tasks. Each image within the dataset is extensively labeled with 50 categories, 1,000 descriptive attributes, bounding boxes, and clothing landmarks. The database supports four primary benchmarks: Attribute Prediction, Consumer-to-shop Clothes Retrieval, In-shop Clothes Retrieval, and Fashion Landmark Detection. The data and annotations are also suitable for training and testing models for tasks such as Clothes Detection, Clothes Recognition, and Image Retrieval. Access to some image data requires a signed agreement for non-commercial research purposes.

Key Features

Over 800,000 fashion images
50 clothing categories
1,000 descriptive attributes
Bounding box annotations
Clothing landmark annotations
Cross-pose/cross-domain image pairs
Benchmarks for Attribute Prediction, In-shop Retrieval, Consumer-to-shop Retrieval, Fashion Landmark Detection
Multi-modal annotations (human parsing, keypoints, fine-grained labels, textual descriptions) in DeepFashion-MultiModal

Pros

Largest visual fashion analysis database
Rich annotations for various computer vision tasks
Supports multiple research benchmarks
Includes diverse image types (shop and consumer photos)
DeepFashion-MultiModal offers additional detailed annotations

Cons

Access requires signing a release agreement
Strictly for non-commercial research purposes only
Some data is encrypted and requires password access
No direct API for programmatic access
Images are not property of MMLAB, user responsible for content

Use Cases

Training models for clothes recognition
Developing fashion image retrieval systems
Researching fashion attribute prediction
Creating fashion landmark detection algorithms
Studying human parsing and pose estimation in fashion images

Best For

Computer vision researchers
Academics studying fashion analysis
Developers building fashion-related AI models
Students working on image recognition projects

Platforms: Web

Watch demo on YouTube ↗

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