8 papers
Mixture of Enhanced-View Experts for Multi-Query Vehicle ReID and A Large-Scale Benchmark
Aihua Zheng, Jie Zhen, Chenglong Li +2
Multi-query vehicle ReID aims to leverage complementary information from diverse views for robust feature learning. However, current methods suffer from simplistic feature fusion a…
NEXT: Multi-Grained Mixture of Experts via Text-Modulation for Multi-Modal Object Re-Identification
Shihao Li, Huaibo Huang, Junxian Duan +3
Multi-modal object Re-IDentification (ReID) aims to obtain complete identity features across heterogeneous modalities. However, most existing methods rely on implicit feature fusio…
RefAerial: A Benchmark and Approach for Referring Detection in Aerial Images
Guyue Hu, Hao Song, Yuxing Tong +5
Referring detection refers to locate the target referred by natural languages, which has recently attracted growing research interests. However, existing datasets are limited to gr…
DCG ReID: Disentangling Collaboration and Guidance Fusion Representations for Multi-modal Vehicle Re-Identification
Aihua Zheng, Ya Gao, Shihao Li +2
Multi-modal vehicle Re-Identification (ReID) aims to leverage complementary information from RGB, Near Infrared (NIR), and Thermal Infrared (TIR) modalities to retrieve the same ve…
UGG-ReID: Uncertainty-Guided Graph Model for Multi-Modal Object Re-Identification
Xixi Wan, Aihua Zheng, Bo Jiang +3
Multi-modal object Re-IDentification (ReID) has gained considerable attention with the goal of retrieving specific targets across cameras using heterogeneous visual data sources. A…
ICPL-ReID: Identity-Conditional Prompt Learning for Multi-Spectral Object Re-Identification
Shihao Li, Chenglong Li, Aihua Zheng +2
Multi-spectral object re-identification (ReID) brings a new perception perspective for smart city and intelligent transportation applications, effectively addressing challenges fro…