Search Results for author: Liming Zhao

Found 7 papers, 2 papers with code

Weakly Supervised Learning with Side Information for Noisy Labeled Images

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.

Variational Quantum Circuit Model for Knowledge Graphs Embedding

no code implementations19 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.

Knowledge Graph Embedding Knowledge Graphs +1

Geometry-Aware Scene Text Detection With Instance Transformation Network

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.

General Classification Multi-Task Learning +2

Deeply-Learned Part-Aligned Representations for Person Re-Identification

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.

Person Re-Identification

Deep Convolutional Neural Networks with Merge-and-Run Mappings

4 code implementations23 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.

DeepSaliency: Multi-Task Deep Neural Network Model for Salient Object Detection

no code implementations19 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.

Multi-Task Learning object-detection +4

Metric Learning Driven Multi-Task Structured Output Optimization for Robust Keypoint Tracking

no code implementations4 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.

Computer Vision Metric Learning +1

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