activity
20202024
most citedA heterogeneous branch and multi-level classification network for person re-identification

13 citations · 23 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2024

Vision Mamba Distillation for Low-resolution Fine-grained Image Classification

Yao Chen, Jiabao Wang, Peichao Wang +2

Low-resolution fine-grained image classification has recently made significant progress, largely thanks to the super-resolution techniques and knowledge distillation methods. Howev…

cs.CV2023★ 2 cited

FewSAR: A Few-shot SAR Image Classification Benchmark

Rui Zhang, Ziqi Wang, Yang Li +2

Few-shot learning (FSL) is one of the significant and hard problems in the field of image classification. However, in contrast to the rapid development of the visible light dataset…

cs.CV2022★ 1 cited

Bridge the Gap between Supervised and Unsupervised Learning for Fine-Grained Classification

Jiabao Wang, Yang Li, Xiu-Shen Wei +3

Unsupervised learning technology has caught up with or even surpassed supervised learning technology in general object classification (GOC) and person re-identification (re-ID). Ho…

cs.CV2020★ 7 cited

Grafted network for person re-identification

Jiabao Wang, Yang Li, Shanshan Jiao +2

Convolutional neural networks have shown outstanding effectiveness in person re-identification (re-ID). However, the models always have large number of parameters and much computat…

cs.CV2020★ 13 cited

A heterogeneous branch and multi-level classification network for person re-identification

Jiabao Wang, Yang Li, Yangshuo Zhang +2

Convolutional neural networks with multiple branches have recently been proved highly effective in person re-identification (re-ID). Researchers design multi-branch networks using…