Visual search for retail enables online shoppers to search for products using images, parts of an image, or even pictures taken with their own cameras. Using images or pictures can be a more intuitive and accurate way for consumers to find what they want than text-based queries, especially when they don’t know the name of the product of brand
Understand the Use-case under 5 minutes
Video (1.2 minutes)
How AI-enabled Visual Search can help find Furniture products much faster and in a way that’s very hard to do otherwise (GrokStyle was acquired by Facebook)
Watch
Article (7 minutes)
Brief introduction to the topic: why it’s needed, the role of machine learning in enabling it, and expected business benefits
Read
Article (5 minutes)
It's estimated that the human brain can process an entire image in just 13 milliseconds, meaning they’re processed 6 to 600 times faster than text. Explore how Visual Search leverages this fact in Retail
Read
Get to know more Business and Technical details about the use-case (15-30 minutes)
More detailed introduction covering business and technical aspects
Article (17 minutes)
Great article tackling many aspects about the state, use, and future of Visual Search. Topics include: how it works, main providers and adopters today, how is it used in retail context, and what’s coming next
Visit
Article (22 minutes)
A comprehensive visual search resource for the latest trends, top retail adopters, stats, news, and strategy tips. Include links for many other articles, so it’s good to look through.
Visit
Video (20 minutes)
Why visual search matters, how it affects the customer experiences, and how it works. Presents a live demo searching with images for fashion, furniture, accessories, and more. Shares insights on business impacts and ROI.
WatchCase studies, Organizational Aspects, Return on Investment examples
Case Studies
Fashion brand PrettyLittleThing achieved a 269% ROI in direct revenue, Home decor marketplace Yestersen realized a 186% CVR uplift, Italian fashion retailer Rinascimento saw a 168% uplift in CVR - and more case studies!
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Case Study
Saatchi Art achieved an 11x return on investment, 12% more conversion rate, 20% higher in click through rate.
Read
Article (8 minutes)
What visual-search is, benefits of it for retailers, talk in brief about some case studies and main takeaways
VisitMore details on the technical aspects of the use-case
Article (7 minutes)
Visual search is based on the recognition of objects and the comparison of visual information with known image content. In this article you will know the types of visual search and how it works.
Visit
Video (7 minutes)
Intuitive Explanation for the AI tech empowering Pinterest Lens and the Visual Search capabilities
Watch
Article (3 minutes)
Summarizes Alibaba’s Visual Search architecture and tech described the paper entitled “Visual Search at Alibaba”. Explains Pailitao: an application that applies the principles of visual image search to e-commerce
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Technical resources that will help you implement the use-case (notebooks, tutorials..)
Github Repo
A visual search system used for product retrieval, includes feature extraction, object detection, and product classification.
VisitGithub Repo
A curated list of research papers, datasets, tools, conferences, workshops related to AI for fashion and e-commerce. Look for “Visual Search” for relevant papers
Visit
Article (10 minutes)
Image segmentation model for application to background removal using Tiramisu, one of the most recent types of deep learning architecture. Enable an effective visual search algorithm by neutralizing interference from the images’ varied backgrounds.
VisitArticle (20 minutes)
Introduction to image similarity techniques and levels. Introduces Deep Ranking Architectures, and Sampling Methods.
Visit
Article (5 minutes)
Why we need a clean image database, How to clean up your image database, image tagging, and what automatic product tagging is, and list some tips to optimize your images.
Read
Data Sets you can use to build Demos, POCs, or test Algorithms
This dataset contains exact street2shop pairs and the retrieval sets for 11 clothing categories: bags, belts, dresses, eyewear, footwear, hats, leggings, outerwear, pants, skirts, tops
a dataset of Zalando's article images—consisting of a training set of 60,000 examples and a test set of 10,000 examples. Each example is a 28x28 grayscale image, associated with a label from 10 classes
a comprehensive fashion dataset. It contains 491K diverse images of 13 popular clothing categories from both commercial shopping stores and consumers.
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