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

• October 2022: Recognized as a top reviewer at NeurIPS 2022.
• September 2021: One paper is accepted at SIGGRAPH ASIA 2021.
• August 2020: I finished my summer internship in computational imaging group at Snap Inc.
• July 2019: One paper is accepted for oral presentation at ICCV 2019.

My research interests are in computational imaging and computer vision. I am interested in identifying visible hints offered by our physical surroundings such as interreflections, 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 or those with strong self-occlusions.

We introduce a kaleidoscopic structured light system that generates hundreds of virtual projectors and cameras for full surround 3D scans of intricate objects.

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

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

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

• Teaching Assistant, 15-463/663/862 Computational Photography  -  Fall 2020
• Teaching Assistant, Recitation for 18-290 Signals and Systems  -  Spring 2019, 2020

• Reviewer, CVPR, ICCV, ECCV, BMVC, SIGGRAPH, ICLR, NeurIPS
• Volunteer, Camera Building Workshop as part of Gelfand Outreach Program at CMU (2019)
• Student Volunteer, ACCV 2012; ICCP 2021

• 16-889 Learning for 3D Vision  -  Spring 2022
• 15-868 Physics-based Rendering  -  Spring 2021
• 33-353 Intermediate Optics  -  Fall 2020
• 15-858 Discrete Differential Geometry  -  Spring 2020
• 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

I like this website.