CRCV Brochure The common goal and purpose of the center is to strongly promote basic research in computer vision and its applications in all related areas including National Defense & Intelligence, Homeland Security, Environment Monitoring, Life Sciences and Biotechnology and Robotics. The Mission of CRCV is to: Be the world class leader in research, commercialization, scholarship and education in computer vision Conduct fundamental and applied research upon which future Computer Vision industries can be built. Provide highest quality education and research experience in computer vision at all levels from K-12 to undergraduate to doctoral and postdoctoral levels to develop a highly skilled workforce for Florida’s economic development, More News CRCV Has 6 Papers Accepted to 5th Ranked CVPR According to h-5-Index January 20, 2021 Read More ICPR 2020 Best Scientific Paper Award January 20, 2021 Read More Master of Science in Computer Vision Approved by Board of Governors December 1, 2020 Read More CS PhD graduate and Prof. Shah win SIGMM Test of Time Honorable Mention Award November 12, 2020 Read More More News AI Can Detect COVID-19 in the Lungs Like a Virtual Physician, New Study Shows September 30, 2020 Read More UCF-CMU Team Win HeroX ASAPS Challenge September 24, 2020 Read More Large-scale Human-centric Video Analysis in Complex Events (HiEve) September 8, 2020 Read More Dr. Shah Awarded $1 Million Grant to Help Advance Machine Vision-Learning Technology August 18, 2020 Read More Events Jun 30 3:00 pm Exploring Relationships Between Ground and Aerial Views by Synthesis and Matching Final Examination of Krishna Regmi for the degree of Doctor of Philosophy in Computer Science Download Bifold We have developed deep neural network based architectures to generate cross-view images, e.g. aerial image corresponding to the ground-level scene, and also developed a method… Archived Events Let’s get social Research Highlights Persistent research endeavors by individuals associated to CRCV continue to stir new ideas and technological advances in the domain. We also strive towards disseminating knowledge thorough seminars, presentations and publications. Large-scale Image Geo-Localization Using Dominant Sets Unsupervised Meta-Learning for Few-Shot Image Classification On Symbiosis of Attribute Prediction and Semantic Segmentation
