snap-research/CAT

[CVPR 2021] Teachers Do More Than Teach: Compressing Image-to-Image Models (CAT)

40
/ 100
Emerging

This project helps creators and developers reduce the size of image-to-image AI models used for tasks like changing an image from day to night, applying artistic styles, or converting sketches to realistic photos. It takes a large, pre-trained image transformation model and outputs a significantly smaller, more efficient version suitable for mobile devices or applications where performance is critical. This is ideal for those building interactive visual applications or augmented reality experiences on platforms like Snapchat.

182 stars. No commits in the last 6 months.

Use this if you need to deploy complex image style transfer or transformation AI models directly onto mobile phones or other resource-constrained environments, ensuring they run smoothly without significant latency.

Not ideal if you are developing a new image transformation model from scratch or if your application runs on powerful servers with ample computational resources.

mobile-app-development augmented-reality image-processing visual-effects computational-photography
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 14 / 25

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Stars

182

Forks

20

Language

Python

License

Last pushed

Apr 22, 2022

Commits (30d)

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