This repository offers the official implementation of DiaNA in PyTorch.

In the meantime, check out our related papers if you are interested:

• 【AAAI 2024】 An Empirical Study of CLIP for Text-based Person Search [paper | code]
• 【ACM MM 2023】 Text-based Person Search without Parallel Image-Text Data [paper]
• 【IJCAI 2023】 RaSa: Relation and Sensitivity Aware Representation Learning for Text-based Person Search [paper | code]
• 【ICASSP 2022】 Learning Semantic-Aligned Feature Representation for Text-based Person Search [paper | code]

DiaNA is a novel dialogue-refined cross-modal framework for chat-based person retrieval that leverages two adaptive attribute refiner modules to bottleneck the conversational and visual information for fine-grained cross-modal alignment.

• Release code
• Release checkpoints
• Release dataset (ChatPedes)

If you find this paper useful, please consider staring 🌟 this repo and citing 📑 our paper:

@InProceedings{bai2025chat,
    author    = {Bai, Yang and Ji, Yucheng and Cao, Min and Wang, Jinqiao and Ye, Mang},
    title     = {Chat-based Person Retrieval via Dialogue-Refined Cross-Modal Alignment},
    booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
    month     = {June},
    year      = {2025}
}

This code is distributed under an MIT LICENSE.