BIT: Matching-based Bi-directional Interaction Transformation Network for Visible-Infrared Person Re-Identification

TL;DR

This paper introduces BIT, a novel matching-based bi-directional interaction network for visible-infrared person re-identification, effectively modeling pairwise modality interactions to improve retrieval accuracy under challenging conditions.

Contribution

The paper proposes the first pairwise matching-driven interaction approach for VI-ReID, utilizing an encoder-decoder architecture for explicit cross-modality feature interaction.

Findings

Achieves state-of-the-art performance on multiple VI-ReID benchmarks.

Effectively models complex modality correlations under distribution shifts.

Demonstrates robustness with fewer infrared samples.

Abstract

Visible-Infrared Person Re-Identification (VI-ReID) is a challenging retrieval task due to the substantial modality gap between visible and infrared images. While existing methods attempt to bridge this gap by learning modality-invariant features within a shared embedding space, they often overlook the complex and implicit correlations between modalities. This limitation becomes more severe under distribution shifts, where infrared samples are often far fewer than visible ones. To address these challenges, we propose a novel network termed Bi-directional Interaction Transformation (BIT). Instead of relying on rigid feature alignment, BIT adopts a matching-based strategy that explicitly models the interaction between visible and infrared image pairs. Specifically, BIT employs an encoder-decoder architecture where the encoder extracts preliminary feature representations, and the decoder performs bi-directional feature integration and query aware scoring to enhance cross-modality correspondence. To our best knowledge, BIT is the first to introduce such pairwise matching-driven interaction in VI-ReID. Extensive experiments on several benchmarks demonstrate that our BIT achieves state-of-the-art performance, highlighting its effectiveness in the VI-ReID task.