CMOT: A cross-modality transformer for RGB-D fusion in person re-identification with online learning capabilities
Person re-identification (reID) is a crucial aspect of intelligent surveillance systems, enabling
the recognition of individuals across non-overlapping camera views. As compared to the …
the recognition of individuals across non-overlapping camera views. As compared to the …
On exploring pose estimation as an auxiliary learning task for Visible–Infrared Person Re-identification
Visible–infrared person re-identification (VI-ReID) has been challenging due to the
existence of large discrepancies between visible and infrared modalities. Most pioneering …
existence of large discrepancies between visible and infrared modalities. Most pioneering …
A visible-infrared clothes-changing dataset for person re-identification in natural scene
Person re-identification (Re-ID) has been widely used in intelligent surveillance systems,
aiming at retrieving specific pedestrian images across different cameras. Although existing …
aiming at retrieving specific pedestrian images across different cameras. Although existing …
Enhancing long-term person re-identification using global, local body part, and head streams
This work addresses the task of long-term person re-identification. Typically, person re-
identification assumes that people do not change their clothes, which limits its applications …
identification assumes that people do not change their clothes, which limits its applications …
Channel enhanced cross-modality relation network for visible-infrared person re-identification
W Song, X Wang, W Wu, Y Zhang, F Liu - Applied Intelligence, 2025 - Springer
Visible-infrared person re-identification (VI Re-ID) is designed to perform pedestrian retrieval
on non-overlapping visible-infrared cameras, and it is widely employed in intelligent …
on non-overlapping visible-infrared cameras, and it is widely employed in intelligent …
Visible-infrared Cross-modality Person Re-identification via Adaptive Weighted Triplet Loss and Progressive Training
L Sone, M Yu, D Sun, X Zhong - IEEE Access, 2024 - ieeexplore.ieee.org
Visible-infrared cross-modality person re-identification (VI-ReID) aims to search the same
person images across multiple non-overlapping cameras of different modalities, which has a …
person images across multiple non-overlapping cameras of different modalities, which has a …
Learning differentiable categorical regions with Gumbel-Softmax for person re-identification
W Yang, P Xu - Neurocomputing, 2025 - Elsevier
Locating diverse body parts and perceiving part visibility are essential to person re-
identification (re-ID). Most existing methods employ an extra model, eg, pose estimation or …
identification (re-ID). Most existing methods employ an extra model, eg, pose estimation or …
Enhancing Person Re-identification Across Modalities with Local and Global Feature Correlation
L Li, N Wu, Z Wang, X Liu - 2023 8th International Conference …, 2023 - ieeexplore.ieee.org
We investigate the challenging problem of visible infrared person re-identification (VI-ReID).
VI-ReID addresses pedestrian retrieval by matching images across different modalities …
VI-ReID addresses pedestrian retrieval by matching images across different modalities …
On Exploring Pose Estimation as an Auxiliary Learning Task for Visible-Infrared Person Re-Identificationon Exploring Pose Estimation as an Auxiliary Learning Task
Visible-infrared person re-identification (VI-ReID) has been challenging due to the existence
of large discrepancies between visible and infrared modalities. Most pioneering approaches …
of large discrepancies between visible and infrared modalities. Most pioneering approaches …
Cross-Modality Average Precision Optimization for Visible Thermal Person Re-Identification
Metric learning is a popular mechanism to address the cross-modality discrepancy and intra-
class variations in visible thermal person re-identification (VT-ReID). However, existing …
class variations in visible thermal person re-identification (VT-ReID). However, existing …