# A Similarity Inference Metric for RGB-Infrared Cross-Modality Person Re-identification

arXiv: https://arxiv.org/abs/2007.01504 · HTML: https://mlsanity.com/paper/2007.01504/

## Key facts

- Cited by 14 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 Jul 2020.

## Built on by (most cited first, 14 of 14)

- [PartMix: Regularization Strategy to Learn Part Discovery for Visible-Infrared Person Re-identification](https://mlsanity.com/paper/2304.01537/) (2023)
- [Fast Continual Multi-View Clustering with Incomplete Views](https://mlsanity.com/paper/2306.02389/) (2023)
- [MSO: Multi-Feature Space Joint Optimization Network for RGB-Infrared Person Re-Identification](https://mlsanity.com/paper/2110.11264/) (2021)
- [Deep High-Resolution Representation Learning for Cross-Resolution Person Re-identification](https://mlsanity.com/paper/2105.11722/) (2021)
- [Exploring Homogeneous and Heterogeneous Consistent Label Associations for Unsupervised Visible-Infrared Person ReID](https://mlsanity.com/paper/2402.00672/) (2024)
- [Visible-Infrared Person Re-Identification Using Privileged Intermediate Information](https://mlsanity.com/paper/2209.09348/) (2022)
- [Bridging the Gap: Multi-Level Cross-Modality Joint Alignment for Visible-Infrared Person Re-Identification](https://mlsanity.com/paper/2307.08316/) (2023)
- [Adaptive Generation of Privileged Intermediate Information for Visible-Infrared Person Re-Identification](https://mlsanity.com/paper/2307.03240/) (2023)
- [Cross-Modality Earth Mover's Distance for Visible Thermal Person Re-Identification](https://mlsanity.com/paper/2203.01675/) (2022)
- [YYDS: Visible-Infrared Person Re-Identification with Coarse Descriptions](https://mlsanity.com/paper/2403.04183/) (2024)
- [CycleTrans: Learning Neutral yet Discriminative Features for Visible-Infrared Person Re-Identification](https://mlsanity.com/paper/2208.09844/) (2022)
- [Learning Cross-modality Information Bottleneck Representation for Heterogeneous Person Re-Identification](https://mlsanity.com/paper/2308.15063/) (2023)
- [Transferring Modality-Aware Pedestrian Attentive Learning for Visible-Infrared Person Re-identification](https://mlsanity.com/paper/2312.07021/) (2023)
- [Blurring Modal Boundaries: A Unified Survey from Single- to Multi-Modal Person Re-ldentification](https://mlsanity.com/paper/2607.14821/) (2026)

## Abstract (arXiv)

RGB-Infrared (IR) cross-modality person re-identification (re-ID), which aims to search an IR image in RGB gallery or vice versa, is a challenging task due to the large discrepancy between IR and RGB modalities. Existing methods address this challenge typically by aligning feature distributions or image styles across modalities, whereas the very useful similarities among gallery samples of the same modality (i.e. intra-modality sample similarities) is largely neglected. This paper presents a novel similarity inference metric (SIM) that exploits the intra-modality sample similarities to circumvent the cross-modality discrepancy targeting optimal cross-modality image matching. SIM works by successive similarity graph reasoning and mutual nearest-neighbor reasoning that mine cross-modality sample similarities by leveraging intra-modality sample similarities from two different perspectives. Extensive experiments over two cross-modality re-ID datasets (SYSU-MM01 and RegDB) show that SIM achieves significant accuracy improvement but with little extra training as compared with the state-of-the-art.