PCA-Based Knowledge Distillation Towards Lightweight and Content-Style Balanced Photorealistic Style Transfer Models

Author:

Chiu Tai-Yin1,Gurari Danna2

Affiliation:

1. University of Texas at Austin

2. University of Colorado Boulder

Publisher

IEEE

Reference50 articles.

1. Avatar-Net: Multi-scale Zero-Shot Style Transfer by Feature Decoration

2. Lightweight neural net-works from pca & Ida based distilled dense neural networks;ei amine seddik;2020 IEEE International Conference on Image Processing (ICIP),0

3. Near infrared reflectance spectroscopy for assessment of spatial soil variation in an agricultural field

4. Apprentice: Using knowledge distillation techniques to improve low-precision network ac-curacy;mishra;ArXiv Preprint,2017

5. Im-proved knowledge distillation via teacher assistant;mirzadeh;Pro-ceedings of the AAAI Conference on Artificial Intelligence,0

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1. KBStyle: Fast Style Transfer Using a 200 KB Network With Symmetric Knowledge Distillation;IEEE Transactions on Image Processing;2024

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3. PanoStyle: Semantic, Geometry-Aware and Shading Independent Photorealistic Style Transfer for Indoor Panoramic Scenes;2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW);2023-10-02

4. Modernizing Old Photos Using Multiple References via Photorealistic Style Transfer;2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR);2023-06

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