Research talk: Capturing the visual evolution of fashion in space and time
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)
- Track:
- The Future of Search & Recommendation
- Date:
- Speakers:
- Kristen Grauman
- Affiliation:
- University of Texas at Austin
The Future of Search & Recommendation
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Keynote: Universal search and recommendation
Speakers:- Paul Bennett
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Research talk: Learning and pretraining strategies for dense retrieval in search and beyond
Speakers:- Chenyan Xiong
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Research talk: Is phrase retrieval all we need?
Speakers:- Danqi Chen
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Research talk: IGLU: Interactive grounded language understanding in a collaborative environment
Speakers:- Julia Kiseleva
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Research talk: Summarizing information across multiple documents and modalities
Speakers:- Subhojit Som
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Panel: The future of search and recommendation: Beyond web search
Speakers:- Eric Horvitz,
- Nitin Agrawal,
- Soumen Chakrabati
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Research talk: Attentive knowledge-aware graph neural networks for recommendation
Speakers:- Yaming Yang
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Panel: Causality in search and recommendation systems
Speakers:- Emre Kiciman,
- Amit Sharma,
- Dean Eckles
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