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[D] How do you think about use face embeddings in conjunction with Elasticsearch for face matching / face similarity application that same as Microsoft’s celebslikeme.me ?

Now, my team is developing a application quite similarity as https://www.celebslike.me of Microsoft Corp before (2016). We seperate the asual canonical pipeline of face recognition system into 3 phrase:

  • Phase 1: Face Detection + Face Aligment
  • Phase 2: Face Embedding
  • Phase 3: Face matching / Face recognion or something like face similarity.

At (3) we use the technical that is the embedded vectors got from a given model that ours is from Facenet in this case to conjunct with Elasticsearch for similarity search.

We are still implementing above solution for now but personally I want to research some nice solutions (if any) for my knowledge also help to improve our product better.

How do you think about another solution(s) for this phase (3) ?

Any ideas are welcome !

submitted by /u/hosjiu
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.