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Visual search. In 2017, Pinterest introduced a "visual search" function that allows users to search for elements in images (existing pins, existing parts of a photo, or new photos) and guide users to suggested similar content within Pinterest's database.
The system is operated by Amazon EC2, and only requires a cluster of 5 GPU instances to handle daily image uploads onto Pinterest. By using reverse image search, Pinterest is able to extract visual features from fashion objects (e.g. shoes, dress, glasses, bag, watch, pants, shorts, bikini, earrings) and offer product recommendations that look ...
Pinterest simultaneously launches three products related to visual search: (1) Lens, which allows users to take photos of objects to find Pins related those objects; (2) Instant Ideas, a circle button that appears on each Pin that, when tapped, displays related Pins; and (3) Shop the Look, a circle button that appears on each individual item ...
Yasmin Khorram. May 6, 2024 at 2:32 PM. Pinterest is standing out from the crowd by using AI to create positive experiences for users, says its CEO. “We’re trying to prove that you can use AI ...
Visual search is a type of perceptual task requiring attention that typically involves an active scan of the visual environment for a particular object or feature (the target) among other objects or features (the distractors). Visual search can take place with or without eye movements.
He is the co-founder and executive chairman of Pinterest, a visual discovery engine which lets users organize images, links, recipes and other things.
Throughout the 2010s and 2020s, online aesthetics gained increasing popularity, specifically on social media platforms such as Tumblr, Pinterest, Instagram, and TikTok, and often were used by people to express their individuality and creativity. They can also be used to create a sense of community and belonging among people who share the same ...
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Some search engines can automatically identify a limited range of visual content, e.g. faces, trees, sky, buildings, flowers, colours etc. This can be used alone, as in content-based image retrieval , or to augment metadata in an image search.
Treisman distinguishes between two kinds of visual search tasks, "feature search" and "conjunction search". Feature searches can be performed fast and pre-attentively for targets defined by only one feature, such as color, shape, perceived direction of lighting, movement, or orientation.