/deep-feature-rotation

Official implementation of paper Deep Feature Rotation for Multimodal Image Style Transfer [2021 8th NAFOSTED Conference on Information and Computer Science]

Primary LanguagePythonMIT LicenseMIT

Deep Feature Rotation for Multimodal Image Style Transfer

Python 3.6 Packagist Last Commit Maintenance Contributing Ask Me Anything !

image1


This repository contains the official implementation of paper:
Deep Feature Rotation for Multimodal Image Style Transfer
Son Truong Nguyen, Nguyen Quang Tuyen, Nguyen Hong Phuc
In NICS 2021 Oral.

Paper (arXiv version) Paper (IEEE version) Presentation Colab Demo Bibtex

Table of Content

  1. Overview
  2. Getting Started
  3. Results
  4. Extensive results
  5. Citation
  6. Contact

Overview

We propose a simple method for representing style features in many ways called Deep Feature Rotation (DFR), while still achieving effective stylization compared to more complex methods in style transfer. Our approach is a representative of the many ways of augmentation for intermediate feature embedding without consuming too much computational expense.


Model architecture

Model architecture.

Getting started

Demo


Try out in Google Colab

Installation

  • Clone this repository and check the requirements.txt:

    git clone https://github.com/sonnguyen129/deep-feature-rotation
    cd deep-feature-rotation
    pip install -r requirements.txt
  • Inference:

    • Prepare your content image and style image. I provide some in the data/content and data/style and you can try to use them easily.
    • Simply run:
    python train.py --content-path <CONTENT_PATH> --style-path <STYLE_PATH>

    The test results will be saved to ./results by default.

Results

Experimental result in different rotation weight.


image4

Comparison with other methods.

Extensive results

We provide a visual comparison between other rotation angles that do not appear in the paper. The rotation angles will produce a very diverse number of outputs. This has proven the effectiveness of our method with other methods.

image4

Visual comparison in different rotation angles.

Citation

If you find this work useful for your research, please cite:

@INPROCEEDINGS{9701465,  
    author={Nguyen, Son Truong and Tuyen, Nguyen Quang and Phuc, Nguyen Hong},  
    booktitle={2021 8th NAFOSTED Conference on Information and Computer Science (NICS)},   
    title={Deep Feature Rotation for Multimodal Image Style Transfer},   
    year={2021},  
    pages={260-265},  
    doi={10.1109/NICS54270.2021.9701465}
}

Contact

If you have any questions/comments/bug reports, feel free to open a github issue or pull a request or mail to the author Son Truong Nguyen.