13 citations · 27 across the 6 of their papers we have counts for
6 papers
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…
Oriented R-CNN for Object Detection
Xingxing Xie, Gong Cheng, Jiabao Wang +2
Current state-of-the-art two-stage detectors generate oriented proposals through time-consuming schemes. This diminishes the detectors' speed, thereby becoming the computational bo…
A Weakly-Supervised Depth Estimation Network Using Attention Mechanism
Fang Gao, Jiabao Wang, Jun Yu +2
Monocular depth estimation (MDE) is a fundamental task in many applications such as scene understanding and reconstruction. However, most of the existing methods rely on accurately…
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…
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…
Ensemble Feature for Person Re-Identification
Jiabao Wang, Yang Li, Zhuang Miao
In person re-identification (re-ID), the key task is feature representation, which is used to compute distance or similarity in prediction. Person re-ID achieves great improvement…