Scheduled Maintenance on Monday 1/13/2025

Single article sales and account management will be unavailable from 5:00 AM - 7:00 PM ET (09:00 - 23:00 UTC). We apologize for the inconvenience.

IEEE.org
IEEE Xplore
IEEE SA
IEEE Spectrum
More Sites

- Donate
- Personal Sign In

Access provided by:

MIT Libraries

Sign Out

Access provided by:

MIT Libraries

Sign Out

ADVANCED SEARCH

Author details

< Back

Xiancai Xiong

Publications

Citations

Publications by Year

20232024

Co-Authors:

Heqing ChengCongcong DuanYong FengJiaxiang HuangWeijia Jia

Show All Co-Authors (8)

Xiancai Xiong

Affiliation

College of Computer Science

Chongqing University

Chongqing, China

State Key Laboratory of Geo-Information Engineering and Key Laboratory of Surveying and Mapping Science and Geospatial Information Technology of MNR

CASM

Beijing, China

Publication Topics

Contrastive Loss,
Image Retrieval,
Triplet Loss,
Auxiliary Information,
Batch Of Images,
Convolution Kernel,
Convolutional Neural Network,
Cross-modal Retrieval,
Cross-modality Person Re-identification,
Data Retrieval,
Deep Learning,
Deep Metric Learning

Biography

Xiancai Xiong received the Ph.D. degree in instrument science and technology from Chongqing University, Chongqing, China, in 2004.,He is currently the Vice President and a Senior Engineer with the Chongqing Institute of Planning and Natural Resources Investigation and Monitoring, Chongqing, China. His research interests include spatio-temporal big data and intelligent remote sensing monitoring.(Based on document published on 8 December 2022).

Publications

Citations

Publications by Year

20232024

Co-Authors:

Heqing Cheng
Congcong Duan
Yong Feng
Jiaxiang Huang
Weijia Jia

Show All Co-Authors (8)

Author's Published Works

Search History

Showing 1-3 of 3 results

Journals (2)

Conferences (1)

Sort

Filter Results

Show

All Results

Subscribed Content

Open Access Only

Range
Single Year
Yongheng Wang(3)
Baohua Qiang(3)
Mingliang Zhou(3)
Yong Feng(3)
Xiancai Xiong(3)
College of Computer Science, Chongqing University, Chongqing, China(3)
Zhejiang Lab, Hangzhou, China(2)
Chongqing Institute of Planning and Natural Resources Investigation and Monitoring, Chongqing, China(2)
Guangxi Key Laboratory of Trusted Software, Guilin University of Electronic Technology, Guilin, China(2)
Key Laboratory of Monitoring, Evaluation and Early Warning of Territorial Spatial Planning Implementation, Ministry of Natural Resources, Chongqing, China(2)
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)(1)
IEEE Geoscience and Remote Sensing Letters(1)
IEEE Transactions on Industrial Informatics(1)
IEEE(3)
Rhodes Island, Greece(1)
Contrastive Loss(2)
Image Retrieval(2)
Triplet Loss(2)
Auxiliary Information(1)
Batch Of Images(1)

Select All on Page

Sort By

Results

Deep Multiscale Fine-Grained Hashing for Remote Sensing Cross-Modal Retrieval

Jiaxiang Huang;Yong Feng;Mingliang Zhou;Xiancai Xiong;Yongheng Wang;Baohua Qiang

IEEE Geoscience and Remote Sensing Letters

Year: 2024 | Volume: 21 | Journal Article |

HTML

Hashing retrieval is a widely used technique in high spatial resolution remote sensing (RS) images due to its efficient retrieval speed and low memory overhead. However, existing hashing retrieval methods primarily focus on matching multilabel RS images, neglecting the extensive fine-grained semantic information in cross-modal RS data. Moreover, RS images exhibit notable object size differences an...Show More

Deep Multiscale Fine-Grained Hashing for Remote Sensing Cross-Modal Retrieval

Jiaxiang Huang;Yong Feng;Mingliang Zhou;Xiancai Xiong;Yongheng Wang;Baohua Qiang

IEEE Geoscience and Remote Sensing Letters

Year: 2024 | Volume: 21 | Journal Article |

Joint Robust Representation And Generalization Enhancement For Cross-Modality Person Re-Identification

Heqing Cheng;Yong Feng;Mingliang Zhou;Xiancai Xiong;Yongheng Wang;Baohua Qiang

ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Year: 2023 | Conference Paper |

HTML

Cross-modality person re-identification (cm-ReID) aims to match pedestrian images from visible and infrared cameras. Most existing methods ignore data bias due to different cameras and views and overlook the strong dependence between feature maps that hinders modal alignment. In this paper, we propose a unified method named Joint Robust Representation and Generalization Enhancement (RRGE) to allev...Show More

Joint Robust Representation And Generalization Enhancement For Cross-Modality Person Re-Identification

Heqing Cheng;Yong Feng;Mingliang Zhou;Xiancai Xiong;Yongheng Wang;Baohua Qiang

ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Year: 2023 | Conference Paper |

Multilevel Similarity-Aware Deep Metric Learning for Fine-Grained Image Retrieval

Congcong Duan;Yong Feng;Mingliang Zhou;Xiancai Xiong;Yongheng Wang;Baohua Qiang;Weijia Jia

IEEE Transactions on Industrial Informatics

Year: 2023 | Volume: 19, Issue: 8 | Journal Article |

Cited by: Papers (2)

HTML

Fast and accurate image retrieval is an important and challenging task in massive image data scenarios. As the core technology of image retrieval tasks, deep metric learning aims at learning effective embedding representations that possess two properties among data points: positive concentrated and negative separated. In this work, we propose a multilevel similarity-aware method based on deep loca...Show More

Multilevel Similarity-Aware Deep Metric Learning for Fine-Grained Image Retrieval

Congcong Duan;Yong Feng;Mingliang Zhou;Xiancai Xiong;Yongheng Wang;Baohua Qiang;Weijia Jia

IEEE Transactions on Industrial Informatics

Year: 2023 | Volume: 19, Issue: 8 | Journal Article |

IEEE Personal Account

Change username/password

Purchase Details

Payment Options
View Purchased Documents

Profile Information

Communications Preferences
Profession and Education
Technical interests

Need Help?

US & Canada: +1 800 678 4333
Worldwide: +1 732 981 0060
Contact & Support

Follow

A public charity, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.

IEEE Account

Change Username/Password
Update Address

Purchase Details

Payment Options
Order History
View Purchased Documents

Profile Information

Communications Preferences
Profession and Education
Technical Interests

Need Help?

US & Canada: +1 800 678 4333
Worldwide: +1 732 981 0060
Contact & Support

About IEEE Xplore
Contact Us
Help
Accessibility
Terms of Use
Nondiscrimination Policy
Sitemap
Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.
© Copyright 2025 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.