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Awesome-Multi-Modal Object Re-Identification Repository

Welcome to the Awesome-Multi-Modal Object Re-Identification Repository! This repository is dedicated to curating and sharing cutting-edge methods and resources specifically focused on multi-modal object re-identification.

My Papers

  • [AAAI25-DeMo]
    DeMo: Decoupled Feature-Based Mixture of Experts for Multi-Modal Object Re-Identification
    Paper Code
  • [AAAI25-MambaPro]
    MambaPro: Multi-Modal Object Re-identification with Mamba Aggregation and Synergistic Prompt
    Paper Code
  • [CVPR24-EDITOR]
    Magic Tokens: Select Diverse Tokens for Multi-modal Object Re-Identification
    Paper Code
  • [AAAI24-TOP-ReID]
    TOP-ReID: Multi-spectral Object Re-Identification with Token Permutation
    Paper Code

Multi-Modal ReID

Methods

Multi-Modal Object ReID

  • [AAAI25-DeMo]
    DeMo: Decoupled Feature-Based Mixture of Experts for Multi-Modal Object Re-Identification
    Paper Code
  • [AAAI25-MambaPro]
    MambaPro: Multi-Modal Object Re-identification with Mamba Aggregation and Synergistic Prompt
    Paper Code
  • [TCSVT24-RSCNet]
    Representation Selective Coupling via Token Sparsification for Multi-Spectral Object Re-Identification
    Paper
  • [ESWA25-LRMM]
    LRMM: Low rank multi-scale multi-modal fusion for person re-identification based on RGB-NI-TI
    Paper
  • [Sensors24-MambaReID]
    MambaReID: Exploiting Vision Mamba for Multi-Modal Object Re-Identification
    Paper
  • [CVPR24-EDITOR]
    Magic Tokens: Select Diverse Tokens for Multi-modal Object Re-Identification
    Paper Code
  • [AAAI24-TOP-ReID]
    TOP-ReID: Multi-spectral Object Re-Identification with Token Permutation
    Paper Code
  • [AAAI24-HTT]
    Heterogeneous Test-Time Training for Multi-Modal Person Re-identifcation
    Paper Code
  • [NeurIPS23-UniCat]
    UniCat: Crafting a Stronger Fusion Baseline for Multimodal Re-Identification
    Paper Code
  • [arXiv23-GraFT]
    GraFT: Gradual Fusion Transformer for Multimodal Re-Identification
    Paper Code

Multi-Modal Person ReID

  • [MLCCIM23-MMCF]
    Multimodal Consistency Co-Assisted Training for Person Re-Identification
    Paper
  • [ICSP23-LRFNet]
    Low-rank Fusion Network for Multi-modality Person Re-identification
    Paper
  • [TNNLS23-DENet]
    Dynamic Enhancement Network for Partial Multi-modality Person Re-identification
    Paper
  • [AAAI22-IEEE]
    Interact, Embed, and EnlargE: Boosting Modality-Specific Representations for Multi-Modal Person Re-identification
    Paper Code
  • [AAAI21-PFNet]
    Robust Multi-Modality Person Re-identification
    Paper

Multi-Modal Vehicle ReID

  • [Inform Fusion24-FACENet]
    Flare-aware cross-modal enhancement network for multi-spectral vehicle Re-identification
    Paper Code
  • [Sensors23-PHT]
    Progressively Hybrid Transformer for Multi-Modal Vehicle Re-Identification
    Paper
  • [TITS23-GPFNet]
    Graph-based progressive fusion network for multi-modality vehicle re-identification
    Paper
  • [Inform Fusion22-CCNet]
    Multi-spectral Vehicle Re-identification with Cross-directional Consistency Network and A High-quality Benchmark
    Paper Code
  • [ICSP22-GAFNet]
    Generative and attentive fusion for multi-spectral vehicle re-identification
    Paper
  • [AAAI20-HAMNet]
    Multi-Spectral Vehicle Re-Identification: A Challenge
    Paper Code

Datasets

Multi-Modal Person ReID

Multi-Modal Vehicle ReID

Star History

Star History Chart

Acknowledgments

I want to express my gratitude to the academic community and everyone contributing to the advancement of multi-modal object re-identification research.

Contact

Feel free to reach out if you have any questions, suggestions, or collaboration proposals:

Citation

If you find our work useful in your research, please consider citing our papers:

@inproceedings{wang2024top,
  title={TOP-ReID: Multi-spectral Object Re-Identification with Token Permutation},
  author={Wang, Yuhao and Liu, Xuehu and Zhang, Pingping and Lu, Hu and Tu, Zhengzheng and Lu, Huchuan},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={38},
  number={6},
  pages={5758--5766},
  year={2024}
}

@InProceedings{Zhang_2024_CVPR,
    author    = {Zhang, Pingping and Wang, Yuhao and Liu, Yang and Tu, Zhengzheng and Lu, Huchuan},
    title     = {Magic Tokens: Select Diverse Tokens for Multi-modal Object Re-Identification},
    booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
    month     = {June},
    year      = {2024},
    pages     = {17117-17126}
}