Gofind AI

Snap a picture and find similar items to buy instantly

4 followers

Gofind AI gallery image
Gofind AI gallery image
Gofind AI gallery image
Gofind AI gallery image
Gofind AI gallery image
Gofind AI gallery image
Gofind AI gallery image
Gofind AI gallery image
Launch tags:iOSProductivityFashion
Launch Team
Unblocked AI Code Review
Unblocked AI Code Review
High-signal comments based on your team's context
Promoted

What do you think? …

Xander Schultz
I think a potential compelling use case is integrating this with Instagram likes data to create a new mobile-first pinterest
Manindra Majumdar
@xanderschultz great idea! it already works with a screenshot & upload from instagram
Rotem Yakir
Aidan Wolf
Results are in the [ballpark] I didn't get any matches after a few dozen photos, but I do like where this is going. Good mvp.
Manindra Majumdar
@capsuledev1 thanks, working on it!
Manindra Majumdar
Rishabh Bose
Pretty impressive... Waiting for when you release AR Shopping... Best of luck.
Manindra Majumdar
@rishabh_bose yup working on it, you read our mind! we are talking to a few AR companies for a demo
Brian Mandel
How does this differ from Pomika? http://pomika.com/tech
David G Ortega
We are actually more interested in how to integrate with Instagram than to create an app. If you are curious about our technology I can say that is mostly composed by two pieces: a deep learning descriptor called deepDNA and the street to shop solver that uses deepDNA. DeepDNA is every efficient in computation and merges image features and text features (word embeddings) so contains a lot of information. It captures incredible semantics, not just only visual features. The recommendations are mindblowing. But our biggest technology improvement is probably how we work with natural images. Mostly all the visual technologies out there are doing the following pipeline: Product extraction and reverse image search. We started doing this also. We developed technology based on top of state-of-the-art segmentation / object detection papers... However my opinion is that this pipeline is very hard to make it work for every single scenario (partial products to full human images). It can work apparently well, but again, very difficult to make it work always. We also want to cover every space, including home design and annotate images does not sound even realistic to me. So we had to think out of the box to not doing what we consider a mistake. We still use RPN's but more as an attention model. I would say that our approach to solve the street to shop problem is more RNN than CNN. Believe me, we are working hard to make that game changer ;)
Manindra Majumdar
Download link for beta iOS App https://itunes.apple.com/us/app/...
12
Next
Last