6 papers
Expandable, Compressible, Mineable: Open-World Thermal Image Restoration
Pu Li, Huafeng Li, Yafei Zhang +3
In open-world settings, thermal infrared (TIR) image degradations continuously emerge and evolve, while most existing all-in-one restoration methods are built on a closed-set assum…
Hierarchical Prompt Learning for Image- and Text-Based Person Re-Identification
Linhan Zhou, Shuang Li, Neng Dong +3
Person re-identification (ReID) aims to retrieve target pedestrian images given either visual queries (image-to-image, I2I) or textual descriptions (text-to-image, T2I). Although b…
DINOv2 Driven Gait Representation Learning for Video-Based Visible-Infrared Person Re-identification
Yujie Yang, Shuang Li, Jun Ye +3
Video-based Visible-Infrared person re-identification (VVI-ReID) aims to retrieve the same pedestrian across visible and infrared modalities from video sequences. Existing methods…
Diverse Semantics-Guided Feature Alignment and Decoupling for Visible-Infrared Person Re-Identification
Neng Dong, Shuanglin Yan, Liyan Zhang +1
Visible-Infrared Person Re-Identification (VI-ReID) is a challenging task due to the large modality discrepancy between visible and infrared images, which complicates the alignment…
ShapeSpeak: Body Shape-Aware Textual Alignment for Visible-Infrared Person Re-Identification
Shuanglin Yan, Neng Dong, Shuang Li +3
Visible-Infrared Person Re-identification (VIReID) aims to match visible and infrared pedestrian images, but the modality differences and the complexity of identity features make i…
Embedding and Enriching Explicit Semantics for Visible-Infrared Person Re-Identification
Neng Dong, Shuanglin Yan, Liyan Zhang +1
Visible-infrared person re-identification (VIReID) retrieves pedestrian images with the same identity across different modalities. Existing methods learn visual content solely from…