# StreetStyle: Exploring world-wide clothing styles from millions of photos

arXiv: https://arxiv.org/abs/1706.01869 · HTML: https://mlsanity.com/paper/1706.01869/

## Key facts

- Cited by 16 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Jun 2017.

## Built on by (most cited first, 16 of 16)

- [What's in a Decade? Transforming Faces Through Time](https://mlsanity.com/paper/2210.06642/) (2022)
- [From Culture to Clothing: Discovering the World Events Behind A Century of Fashion Images](https://mlsanity.com/paper/2102.01690/) (2021)
- [Diffusion Models as Data Mining Tools](https://mlsanity.com/paper/2408.02752/) (2024)
- [Exploring AI in Fashion: A Review of Aesthetics, Personalization, Virtual Try-On, and Forecasting](https://mlsanity.com/paper/2101.08301/) (2021)
- [Smart Fashion: A Review of AI Applications in the Fashion & Apparel Industry](https://mlsanity.com/paper/2111.00905/) (2021)
- [Leveraging Multiple Relations for Fashion Trend Forecasting Based on Social Media](https://mlsanity.com/paper/2105.03299/) (2021)
- [GLAMI-1M: A Multilingual Image-Text Fashion Dataset](https://mlsanity.com/paper/2211.14451/) (2022)
- [fAshIon after fashion: A Report of AI in Fashion](https://mlsanity.com/paper/2105.03050/) (2021)
- [Automatic Image Content Extraction: Operationalizing Machine Learning in Humanistic Photographic Studies of Large Visual Archives](https://mlsanity.com/paper/2204.02149/) (2022)
- [Social Media Fashion Knowledge Extraction as Captioning](https://mlsanity.com/paper/2309.16270/) (2023)
- [Visual Chronicles: Using Multimodal LLMs to Analyze Massive Collections of Images](https://mlsanity.com/paper/2504.08727/) (2025)
- [Fashionpedia-Taste: A Dataset towards Explaining Human Fashion Taste](https://mlsanity.com/paper/2305.02307/) (2023)
- [Fashionpedia-Ads: Do Your Favorite Advertisements Reveal Your Fashion Taste?](https://mlsanity.com/paper/2305.02360/) (2023)
- [Face Clustering for Connection Discovery from Event Images](https://mlsanity.com/paper/2309.01092/) (2023)
- [UNICON: A unified framework for behavior-based consumer segmentation in e-commerce](https://mlsanity.com/paper/2309.13068/) (2023)
- [Agentic Personalized Fashion Recommendation in the Age of Generative AI: Challenges, Opportunities, and Evaluation](https://mlsanity.com/paper/2508.02342/) (2025)

## Abstract (arXiv)

Each day billions of photographs are uploaded to photo-sharing services and social media platforms. These images are packed with information about how people live around the world. In this paper we exploit this rich trove of data to understand fashion and style trends worldwide. We present a framework for visual discovery at scale, analyzing clothing and fashion across millions of images of people around the world and spanning several years. We introduce a large-scale dataset of photos of people annotated with clothing attributes, and use this dataset to train attribute classifiers via deep learning. We also present a method for discovering visually consistent style clusters that capture useful visual correlations in this massive dataset. Using these tools, we analyze millions of photos to derive visual insight, producing a first-of-its-kind analysis of global and per-city fashion choices and spatio-temporal trends.