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[P] Implementing Stand-Alone Self-Attention in Vision Models paper using Pytorch

Hi, I’m Myeongjun Kim. My major is Computer Vision using Deep Learning. “Stand-Alone Self-Attention in Vision Models” paper published on 13 Jun 2019. This paper was presented by the Google Research Brain Team. I implemented this paper in pytorch. Currently I am experimenting with a CIFAR-10 dataset. (training 30 epoch, Accuracy: 88.4%) The experiment is still in progress. I could see that the learning was very good. Many researches seem to use the Attention Module.

There are some parts that are not currently implemented, and some parts have not yet been experimented. I would appreciate a lot of feedback.

[Github URL: https://github.com/leaderj1001/Stand-Alone-Self-Attention]

Thank you so much 🙂

submitted by /u/leaderj1001
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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.