🖼️ ⁉️ Distortion Generator

| [Journal Paper] | [Conference Paper] | [Papers with Code] | [Citation] |

Neural network for creating distortion while keeping embeddings as close as possible. Part of the research paper "Unrecognizable Yet Identifiable: Image Distortion with Preserved Embeddings."

The code is written in TensorFlow v2.12.

ℹ️ Paper info

Unrecognizable Yet Identifiable: Image Distortion with Preserved Embeddings

Dmytro Zakharov¹, Oleksandr Kuznetsov^1,2, Emanuele Frontoni²

¹ V. N. Karazin Kharkiv National University, Ukraine

² University of Macerata, Italy

Preprint at arXiv

📁 Structure

The project is structured as follows:

File/Folder	Description
cli.py	CLI for running training or evaluation
src	All source files for training and evaluating the models
images	Images with example generations, evaluation plots etc.
hyperparams_embedding.json	Hyperparameters for training the embedding model
hyperparams_generator.json	Hyperparameters for training the generator model
dataset	Dataset which was used for training (actually, the portion of it since we do not want to put everything into the repository)
models	Models' weights after the training. Just so you know, the newest versions of the generator are not included since they weigh too much for GitHub to handle.

Citation

@misc{zakharov2024unrecognizable,
      title={Unrecognizable Yet Identifiable: Image Distortion with Preserved Embeddings}, 
      author={Dmytro Zakharov and Oleksandr Kuznetsov and Emanuele Frontoni},
      year={2024},
      eprint={2401.15048},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}