Byeongjoo Ahn

I am a Ph.D. candidate majoring in Electrical and Computer Engineering at Carnegie Mellon University. I am fortunate to be advised by Prof. Aswin C. Sankaranarayanan and Prof. Ioannis Gkioulekas, and supported by KFAS Scholarship.

I received B.S. in Electrical and Computer Engineering and M.S. in Electrical Engineering and Computer Science at Seoul National University, working with Prof. Kyoung Mu Lee. I also spent wonderful three years as a research scientist of the Center for Imaging Media Research at Korea Institute of Science and Technology.

My first name pronounces as Be-Young-Joo.

Email  /  CV  /  Google Scholar  /  LinkedIn  /  GitHub

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News
  • July 2019: One paper was accepted for oral presentation at ICCV 2019.
Research

My research interests are in computational imaging and computer vision. I am interested in identifying visible hints offered by our physical surroundings, and developing imaging systems extending the visibility far beyond human ability such as the reconstruction of objects that are not in the direct line of sight.

"Convolutional Approximations to the General Non-Line-of-Sight Imaging Operator"
Byeongjoo Ahn, Akshat Dave, Ashok Veeraraghavan, Ioannis Gkioulekas, Aswin C. Sankaranarayanan
IEEE/CVF International Conference on Computer Vision (ICCV), 2019   (Oral Presentation)
Project Page / Paper / Supplement / BibTeX

A computationally efficient technique for NLOS imaging based on a derivation that shows the Gram of the measurement operator is convolutional.

"Occlusion-Aware Video Deblurring with a New Layered Blur Model"
Byeongjoo Ahn, Tae Hyun Kim, Wonsik Kim, Kyoung Mu Lee
Technical Report, 2016
arXiv / Paper / BibTeX

Occlusion-aware deblurring method for scenes with occluding objects using a carefully designed layered blur model that reflects actual blur generation process.

"Reduced Illumination Patterns for Acquisition of Specular and Diffuse Normal Maps"
Byeongjoo Ahn, Junghyun Cho, Taekyung Yoo, Ig-Jae Kim
ACM SIGGRAPH Asia Posters, 2016
Paper / BibTeX

Acquisition of specular and diffuse normal maps from minimal number of polarized images by removing the redundancy in four reflectances under XYZ-gradient and constant patterns.

"Dynamic Scene Deblurring"
Tae Hyun Kim, Byeongjoo Ahn, Kyoung Mu Lee
IEEE International Conference on Computer Vision (ICCV), 2013
Paper / BibTeX

Dynamic scene deblurring method estimating the latent image as well as different blur motions and their soft segmentations jointly.

Teaching
  • Teaching Assistant, Recitation for 18-290 Signals and Systems  -  Spring 2019
Services
  • Reviewer, CVPR 2019; ICCV 2019; BMVC 2019
  • Volunteer, Camera Building Workshop as part of Gelfand Outreach Program at CMU (2019)
  • Student Volunteer, ACCV 2012
Graduate Coursework
  • 18-771 Linear Systems  -  Fall 2019
  • 10-707 Deep Learning  -  Spring 2019
  • 10-725 Convex Optimization  -  Fall 2018
  • 16-823 Physics based Methods in Vision  -  Spring 2018
  • 10-701 Introduction to Machine Learning  -  Spring 2018
  • 16-720B Computer Vision  -  Fall 2017
  • 18-793 Image and Video Processing  -  Fall 2017
  • 36-705 Intermediate Statistics  -  Fall 2017

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