Research talk: Capturing the visual evolution of fashion in space and time
- Kristen Grauman | University of Texas at Austin
- Microsoft Research Summit 2021 | The Future of Search & Recommendation
The fashion domain is a magnet for computer vision. New vision problems are emerging in step with the fashion industry’s rapid evolution towards an online, social, and personalized business. Style models, trend forecasting, and recommendation all require visual understanding with rich detail and subtlety. Not only can this visual understanding benefit individual users, but when analyzed across large-scale multi-modal data, it also can reveal how cultural factors and world events dynamically influence what people around the world wear. I will present our work investigating fashion forecasting and influence from photos. We introduce models to quantify which cultural factors (as captured by millions of news articles) most affect the clothes people chose to wear across a century of vintage clothing photos, as well as models that discover from web photos the way styles propagate from one city to another over time. This work is a first step towards data-driven, quantitative understanding of how our clothes reflect our ever-changing culture and our interconnected world.
Learn more about the 2021 Microsoft Research Summit: https://Aka.ms/researchsummit (opens in new tab)
The Future of Search & Recommendation
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Keynote: Universal search and recommendation
- Paul Bennett
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Research talk: System frontiers for dense retrieval
- Jason Li,
- Knut Risvik
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Research talk: Domain-specific pretraining for vertical search
- Tristan Naumann
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Panel: The future of search and recommendation: Beyond web search
- Eric Horvitz,
- Nitin Agrawal,
- Soumen Chakrabati
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Panel: Causality in search and recommendation systems
- Emre Kiciman,
- Amit Sharma,
- Dean Eckles
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