Bacground removal with deep learning

Deep Learning
#1

Hi Guys,
Me and Alon Burg have released an alpha version of GreenScreen.AI - a background removal app, which we’ve been working on in the last few months.
We are also releasing 3 detailed blogposts about our work process.
You are more than welcomed to read, expereince and comment!
For any questions or inquires, feel free to contact us :slight_smile:
The app
https://greenscreen-ai.boorgle.com/
The Blog posts -
machine learning:
https://medium.com/@gidishperber/background-removal-with-deep-learning-c4f2104b3157
Deployment:
https://medium.com/@burgalon/deploying-your-keras-model-35648f9dc5fb
https://medium.com/@burgalon/deploying-your-keras-model-using-keras-js-2e5a29589ad8

5 Likes
#2

Medium link to first post doesn’t work for me?

#3

Thanks, fixed it

#4

We’re considering if we should try to pursue Matting with Deep Learning as a 2nd step for improving the background removal.
Anyone has experience with combining semantic segmentation with DL matting?

2 Likes
#5

Thanks for the keywords and your projects, I have one more thing to play with in the future :slight_smile:. If I can train the matting model successful I will send you a message.

#6

You guys might have fun with this background removal Kaggle competition?

#7

@brendan - yep we’re trying to come up with some new architecture or combination of NN to nail this.

I’m wondering if we have a good chance of winning 1st-3rd place with simply segmentation, as it seems there are people who are more experienced then us in ensembling and training multitude of models to find the optimal hyperparameters.

#8

@burgalon I used a U-net on 512x512 images and it worked very well. Maybe passing in a 1024x1024 image will improve the results.

Have you tried using tiramisu on it?

#9

Hi burgalon,
Could you please share the model implementation code.