Mingze Xu

Mingze Xu

徐 铭 泽


Ph.D. Candidate

School of Informatics, Computing, and Engineering

Indiana University


IU Computer Vision Lab

611 N Park Ave

Bloomington, IN 47408

mx6 [at] indiana [dot] edu


[Research] [Publications] [Projects] [Teaching] [CV]

News

  • 03/2018:   Start my research internship at Honda Research Institute USA (HRI).

  • 11/2017:   Successfully acquire Ph.D. candidacy at Indiana University.

  • 10/2017:   Two papers accepted to Round 1 of WACV 2018.

  • 05/2017:   One paper accepted to ICIP 2017.

  • 05/2017:   Start my research internship at Midea Corporate Research Center (CRC).

  • 02/2017:   One paper accepted to CVPR 2017.

Research

Hi, I'm Mingze. I'm a third-year Ph.D. candidate of School of Informatics, Computing, and Engineering at Indiana University. My advisor is Prof. David Crandall. I received a Master degree in Computer Science from Indiana University (2014) and a Bachelor degree in Software Engineering from Jilin University (2012).

My research is primarily in the area of Computer Vision and Deep Learning. In particular, I focus on applying deep neural networks to recognition tasks in videos, which improves the performance of object detection and segmentation close to that of human. I'm also working on understanding large-scale data from Polar Science, such as 3D object segmentation and reconstruction from sequential tomograms.

Publications

Computer Vision Conference Papers:

  • Mingze Xu, Aidean Sharghi, Xin Chen, and David Crandall, "Fully-Coupled Two-Stream Spatiotemporal Networks for Extremely Low Resolution Action Recognition," IEEE Winter Conference on Applications of Computer Vision (WACV), 2018. [PDF]

  • Mingze Xu, Chenyou Fan, John Paden, Geoffrey Fox, and David Crandall, "Multi-Task Spatiotemporal Neural Networks for Structured Surface Reconstruction," IEEE Winter Conference on Applications of Computer Vision (WACV), 2018. [PDF]

  • Mingze Xu, David Crandall, Geoffrey Fox, and John Paden, "Automatic Estimation of Ice Bottom Surfaces from Radar Imagery," IEEE International Conference on Image Processing (ICIP), 2017. [PDF]

  • Chenyou Fan, Jangwon Lee, Mingze Xu, Krishna Kumar Singh, Yong Jae Lee, David Crandall, and Michael Ryoo, "Identifying First-person Camera Wearers in Third-person Videos," IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017. [PDF] [Project page]

Remote Sensing Conference Papers:

  • Victor Berger, Mingze Xu, David Crandall, John Paden, and Geoffrey Fox, "Automated Tracking of 2D and 3D Ice Radar Imagery using Viterbi and TRW-S," IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2018. [PDF]

  • Mohanad Al-Ibadi, Jordan Sprick, Sravya Athinarapu, Victor Berger, Theresa Stumpf, John Paden, Carl Leuschen, Fernando Rodriguez, Mingze Xu, David Crandall, Geoffrey Fox, David Burgess, Martin Sharp, Luke Copland, and Wesley Van Wychen, "Crossover Analysis and Automated Layer-tracking Assessment of the Extracted DEM of the Basal Topography of the Canadian Arctic Archipelago Ice Caps," IEEE Radar Conference, 2018. [PDF]

  • Mohanad Al-Ibadi, Jordan Sprick, Sravya Athinarapu, Theresa Stumpf, John Paden, Carl Leuschen, Fernando Rodriguez, Mingze Xu, David Crandall, Geoffrey Fox, David Burgess, Martin Sharp, Luke Copland, and Wesley Van Wychen, "DEM Extraction of the Basal Topography of the Canadian Archipelago Ice Caps via 2D Automated Layer-tracking," IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2017. [PDF]

Teaching

Research Mentor:

  • Fall 2017: Undergraduate Research Opportunities in Computing

  • Spring 2017: Undergraduate Research Opportunities in Computing

Associate Instructor:

  • Fall 2014: CSCI B351 Introduction to Artificial Intelligence

  • Spring 2014: CSCI B552 Knowledge Based Artificial Intelligence

Last update: 03/2018