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kdwonn authored Aug 4, 2023
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[![arXiv](https://img.shields.io/badge/arXiv-1234.56789-b31b1b.svg)](https://arxiv.org/abs/2211.16761)

This repository contains official source code for our paper:
This repository contains the official source code for our paper:
>[Improving Cross-Modal Retrieval with Set of Diverse Embeddings](https://arxiv.org/abs/2211.16761)
> [Dongwon Kim](https://kdwonn.github.io/),
> [Namyup Kim](https://southflame.github.io/), and
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> CVPR (Highlight), Vancouver, 2023.
## Acknowledgement
Parts of our codes are adopted from following repositories.
Parts of our codes are adopted from the following repositories.

* https://github.com/yalesong/pvse
* https://github.com/fartashf/vsepp
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## Dataset
For now, provided training script is only for Faster-RCNN + bi-GRU experimental setting on COCO dataset.
We use the dataset preparation scripts from https://github.com/kuanghuei/SCAN#download-data.
Place the precomp folder and id_mapping.json under ./data/coco_butd, and vocab file under ./vocab.
Place the precomp folder under ./data/coco_butd, and the vocab file under ./vocab.

## Requirements
You can install requirements using conda.
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