Extending CLIP for Category-to-Image Retrieval in E-commerce

This repository contains the implementation and resources used for the experiments in the paper "Extending CLIP for Category-to-image Retrieval in E-commerce" published at ECIR 2022.

Overview

This project extends the CLIP model to improve category-to-image retrieval tasks in zero-shot vs. fine-tuned settings.

Getting Started

Prerequisites

• Python 3.8+
• PyTorch
• A GPU is recommended for training and evaluation.

Installation

1. Clone the repository:

   git clone https://github.com/<your-repo>/clip-category-retrieval.git  
   cd clip-category-retrieval

2. Install the dependencies:

   pip install -r requirements.txt

License

This repository is licensed under the MIT License. Feel free to use, modify, and distribute the code. If you make significant modifications, please link back to this repository as a courtesy.

Citing and Authors

If you find this repository helpful, please consider citing our paper:

@inproceedings{hendriksen-2022-extending-clip,
author = {Hendriksen, Mariya and Bleeker, Maurits and Vakulenko, Svitlana and van Noord, Nanne and Kuiper, Ernst and de Rijke, Maarten},
booktitle = {ECIR 2022: 44th European Conference on Information Retrieval},
month = {April},
publisher = {Springer},
title = {Extending CLIP for Category-to-image Retrieval in E-commerce},
year = {2022}}