Changqian Yu (余昌黔)

Changqian Yu is a second-year graduate student majoring in Computer Vision at Huazhong University of Science and Technology. He is pursuing his Master Degree under the supervision of A.P. Changxin Gao and Prof. Nong Sang (2016-2019). He works as a research intern at Megvii (Face++) Inc. mentored by Dr. Gang Yu and supervised by Dr. Jian Sun. His research interests focus on the Computer Vision and Artificial Intelligence, specifically on the topic of Segmentation.

changqian_yu@hust.edu.cn

Interests

  • Artificial Intelligence
  • Computer Vision
  • Segmentation

Education

  • Msc in Computer Vision, 2016
    Huazhong Univ Of Science And Tech
  • Bsc in Automation, 2012
    Shandong University
Changqian Yu

News

Conference

DFN

Learning a Discriminative Feature Network for Semantic Segmentation

Changqian Yu, Jingbo Wang, Chao Peng, Changxin Gao, Gang Yu, Nong Sang
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018
Most existing methods of semantic segmentation still suffer from two aspects of challenges: intra-class inconsistency and inter-class indistinction. To tackle these two problems, we propose a Discriminative Feature Network (DFN), which contains two sub-networks: Smooth Network and Border Network. Specifically, to handle the intra-class inconsistency problem, we specially design a Smooth Network with Channel Attention Block and global average pooling to select the more discriminative features. Furthermore, we propose a Border Network to make the bilateral features of boundary distinguishable with deep semantic boundary supervision. Based on our proposed DFN, we achieve state-of-the-art performance 86.2% mean IOU on PASCAL VOC 2012 and 80.3% mean IOU on Cityscapes dataset.
@inproceedings{Yu_2018_CVPR,
author = {Yu, Changqian and Wang, Jingbo and Peng, Chao and Gao, Changxin and Yu, Gang and Sang, Nong},
title = {Learning a Discriminative Feature Network for Semantic Segmentation},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2018}
}







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