Xueqing Deng

About Me

Hello! I am a PhD candidate in Computer Vision Lab at UC Merced, supervised by Professor Shawn Newsam. Before I came to UC Merced, I received my B.S. degree majoring in Geographic Information System and Remote Sensing from Sun Yat-Sen University, China in June 2016, and worked with Professor Wenkai Li in one-class remote sensing imagery classification.

I am now in job market.

Here is my CV.

Please check my google scholar for a full list of paers.

Research Interests

I am interested in geospatial computer vision problems and applied deep learning. My research interests include but not limited to GAN, semantic segmentation, image classification using aerial images and streetview images.

News and Events

New! 6/23/2021: One paper about neural architecture search on domain adaptation accepted at 1st NAS workshop at CVPR 2021. Four-page short version is available at [link]

New! 5/28/2021: I am co-organizing the 3rd GeoAI Workshop at ACM SIGSPATIAL 2021.

4/17/2021: I gave a presentation on GeoAI invited by Prof. Yu Liu from Peking University, China at Symposium of GeoAI. Great experience to give a live talk with bilibili.

2/25/2021: I will be joining ByteDance Intelligent Creation Lab at Mountain View as a research intern working on neural architecture search this summer!

12/8/2020: I am awarded Graduate Dean Dissertation Fellowship for 2021. Many thanks to the committee and my advisor.

10/18/2020: I am right now serving as ACM SIGSPATIAL webmaster.

9/5/2020 I contributed DANet for semantic segmentation and StyleGAN for image synthesis to GLUON-CV. Please check the [link]!

8/6/2020: One paper on domain adaptation for land-cover classification has been accepted at WACV 2021!

6/1/2020: One paper on spatial explicit deep learning has been accepted at GIScience 2021!

4/28/2020: I passed my qualifying exam and I am a PhD candidate!

12/16/2019: One paper "Multi-Label Remote Sensing Image Retrieval Based on Fully Convolutional Network" has been accepted to IEEE journal JSTARS.

12/10/2019: One paper "Cross-Time and Orientation-Invariant Overhead Image Geolocalization Using Deep Local Features" has been accepted at WACV 2020.

7/8/2019: I participate in AAG Summer School at UIUC and received NSF travel award for the trip. Nice to meet people working on Geographic problems.

4/5/2019: A paper has been accepted at IGARSS 2019 as oral presentation.

11/7/2018: I present my oral at ACM SIGSPATIAL [slides]

8/21/2018: One paper has been accepted at ACM SIGSPATIAL 2018 (oral), What Is It Like Down There? Generating Dense Ground-Level Views and Image Features From Overhead Imagery Using Conditional Generative Adversarial Networks.

New! 5/21/2018: I started my internship at Oak Ridge National Laboratory today, mainly working on domain adaption with adversarial learning on road segmentation using high-resolutional remote sensing images.

New! 5/4/2018: My paper titled "Spatial Morphing Kernel Regression for Feature Interpolation" has been accepted at ICIP 2018.

04/2018: I was sponsored to attend CRA-W 2018 Cohort Workshop in San Francisco.

02/2018: One paper submitted to ICIP 2018. https://arxiv.org/abs/1802.07452

01/2018: I published a new journal paper: One-class remote sensing classification: one-class vs. binary classifiers [pdf].

11/2017: I presented my workshop paper on SIGSPATIAL [slides].

10/2017: I was awarded a NSF student travel grant of ACM SIGSPATIAL 2017.

10/2017: One paper was accepted by ACM SIGSPATIAL Workshop Urban GIS 2017.

10/2017: One paper was accepted by International Journal of Remote Sensing.

8/2017: I changed to PhD program supervised by Professor Shawn Newsam.

5/2017: I was awarded a Bobcat Summer Fellowship, EECS, UC Merced.

12/2016: I got an A+ for CSE 176 Introduction to Machine Learning, a challenging course!

10/2016: Thanks to Professor Newsam, I was supported to participate in ACM SIGSPATIAL 2016.

8/2016: I came to UC Merced to pursue a Master degree in EECS.

6/2016: I received my B.S. degree from Sun Yat-Sen University in China, as well as received a thesis award.