no code implementations • ECCV 2020 • Lele Cheng, Xiangzeng Zhou, Liming Zhao, Dangwei Li, Hong Shang, Yun Zheng, Pan Pan, Yinghui Xu
In many real-world datasets, like WebVision, the performance of DNN based classifier is often limited by the noisy labeled data.
no code implementations • 19 Feb 2019 • Yunpu Ma, Volker Tresp, Liming Zhao, Yuyi Wang
In this work, we propose the first quantum Ans\"atze for the statistical relational learning on knowledge graphs using parametric quantum circuits.
no code implementations • CVPR 2018 • Fangfang Wang, Liming Zhao, Xi Li, Xinchao Wang, DaCheng Tao
Localizing text in the wild is challenging in the situations of complicated geometric layout of the targets like random orientation and large aspect ratio.
1 code implementation • ICCV 2017 • Liming Zhao, Xi Li, Jingdong Wang, Yueting Zhuang
In this paper, we address the problem of person re-identification, which refers to associating the persons captured from different cameras.
Ranked #88 on
Person Re-Identification
on Market-1501
4 code implementations • 23 Nov 2016 • Liming Zhao, Jingdong Wang, Xi Li, Zhuowen Tu, Wen-Jun Zeng
A deep residual network, built by stacking a sequence of residual blocks, is easy to train, because identity mappings skip residual branches and thus improve information flow.
no code implementations • 19 Oct 2015 • Xi Li, Liming Zhao, Lina Wei, Ming-Hsuan Yang, Fei Wu, Yueting Zhuang, Haibin Ling, Jingdong Wang
A key problem in salient object detection is how to effectively model the semantic properties of salient objects in a data-driven manner.
no code implementations • 4 Dec 2014 • Liming Zhao, Xi Li, Jun Xiao, Fei Wu, Yueting Zhuang
As an important and challenging problem in computer vision and graphics, keypoint-based object tracking is typically formulated in a spatio-temporal statistical learning framework.