Enrique Dunn

Associate Professor

School: School of Engineering and Science

Department: Computer Science

Building: Gateway Center

Room: S323

Phone: (201) 216-3382

Fax: (201) 216-8249

Email: edunn@stevens.edu


General Information

Enrique Dunn is an associate professor in the Department of Computer Science. His research focus is on 3D Computer Vision, investigating the geometric and semantic relationships among a 3D scene and a depicting set of images.
Dr. Dunn earned a degree in computer engineering from the Autonomous University of Baja California (Mexico) in 1999. He completed a master’s degree in Computer Science in 2001 and a doctorate in Electronics and Telecommunications in 2006, both from the Ensenada Center for Scientific Research and Higher Education (Mexico). During his doctorate studies, Dr. Dunn carried out research while visiting the French Institute for Research in Computer Science and Control in Rocquencourt. He joined the Department of Computer Science of the University of North Carolina at Chapel Hill as a visiting scholar in 2008, after being awarded a one year Postdoctoral Fellowship for Studies Abroad by the National Council for Science and Technology (Mexico). He remained with UNC-CH CS Department as a postdoctoral researcher until he became a research assistant professor in 2012. Dr. Dunn has authored over 40 papers in international conferences and journals. He is a member of the Editorial Board of Elsevier Journal of Image and Vision Computing. ​​

Institutional Service
  • CPT coordinator Member
  • Graduate Advisor Member
  • High Performance Computing Chair
Professional Service
  • ELSEVIER IMAVIS journal Associate Editor
  • ECCV 2020 Program Committe Area Chair
  • Image and Vision Computing Associate Editor
  • 3DV Conference Area Chair
  • International Conference on Computer Vision ICCV Reviewer
  • IEEE Conference on Computer Vision and Pattern Recognition Reviewer CVPR
Selected Publications
Conference Proceeding
  1. Dunn, E. (2021). VOLDOR-SLAM: For the Times When Feature-Based or Direct Methods Are Not Good Enough. ICRA 2020.
  2. Min, Z.; Yang, Y.; Dunn, E. (2020). VOLDOR: Visual Odometry From Log-Logistic Dense Optical Flow Residuals. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
  3. Xu, X.; Dunn, E. (2019). Discrete Laplace Operator Estimation for Dynamic 3D Reconstruction. Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV).