Krishna Regmi

Senior R&D Engineer

Krishna Regmi is a senior R&D engineer on Kitware’s Computer Vision Team located in Carrboro, North Carolina. Krishna is involved in projects that involve satellite imagery analytics, for example, object detection in satellite imagery with low-shot learning.

Prior to joining Kitware, Krishna was a graduate research and teaching assistant at the University of Central Florida. His research focused on using Generative Adversarial Networks (GANs) to generate images and videos from novel views as well as on image matching and video geolocalization. His work on cross-view image synthesis published at the Conference on Computer Vision and Pattern Recognition (CVPR) in 2018 introduced a novel computer vision problem to the research community. 

While working on his Ph.D., Krishna led the National Geo-Spatial Agency (NGA) research project on image and video geolocalization. He developed a novel solution to cross-view image matching by leveraging generative models to synthesize cross-view images to bridge the domain gap between query ground and gallery aerial images. He was also a research scientist intern for Netflix where he worked on frame deblurring for the application of Personalized Artwork Creation. 

Before earning his master’s degree, Krishna was a lecturer at the Kantipur Engineering College, Tribhuvan University, Nepal where he taught different undergraduate level courses.

Krishna received his Ph.D. in computer science from the University of Central Florida in 2021. In 2015, he received his master’s degree in electrical engineering from Southern Illinois University Edwardsville. Krishna received his bachelor’s degree in electrical and communication engineering from Tribhuvan University in Nepal in 2009 and he was a visiting undergraduate student at the University of Bradford from 2009-2010.

 

Education

Ph.D. in computer science from the University of Central Florida, 2021

M.S. in electrical engineering from Southern Illinois University Edwardsville, 2015

B.S. in electrical and communication engineering from Tribhuvan University, 2009

 

Awards

ORC Doctoral Fellowship presented by the University of Central Florida, 2016-2017

Competitive Graduate Award presented by Southern Illinois University Edwardsville, 2013-2014

 

Invited Talks & External Recognition

Invited Talk, Bridging the Domain Gap for Ground-to-Aerial Image Matching, Moving Cameras Workshop, International Conference on Computer Vision (ICCV), 2019

Get to Know Krishna

What made you want to become a Kitwarean? Since learning about Kitware at a computer vision conference in 2019, I have been fascinated by Kitware’s diverse and challenging computer vision research activities. Due to the very high overlap of my Ph.D. research with Kitware’s research, I was confident that Kitware was the right place for me to thrive.

What do you love most about what you do? I like to bring new perspectives and solutions to new and existing computer vision problems.

Share something interesting about yourself that is not on your resume. I love watching sports. I’m a big fan of tennis, soccer, football, and basketball. I enjoy mountains as much as I enjoy being on the beach.

Professional Associations & Service

  • Reviewer for the Winter Conference on Applications of Computer Vision (WACV), 2020-present
  • Reviewer for the IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020-present
  • Reviewer for the Journal of Big Data, 2020-present

 

Publications

Krishna’s publication list is below. To see all of Kitware’s computer vision publications, please visit the Computer Vision Publications page.

  1. K. Regmi and A. Borji, "Cross-view image synthesis using geometry-guided conditional GANs," Computer Vision and Image Understanding, vol. 187, pp. 102788, Oct. 2019. [URL]
  2. K. Regmi and M. Shah, "Bridging the Domain Gap for Ground-to-Aerial Image Matching," in 2019 IEEE/CVF International Conference on Computer Vision (ICCV), 2019. [URL]
  3. K. Regmi and A. Borji, "Cross-View Image Synthesis Using Conditional GANs," in 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018. [URL]

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