Byeongjoo Ahn

I am a research scientist at Apple in Seattle. I received my Ph.D. from Carnegie Mellon University, where I was advised by Aswin C. Sankaranarayanan and Ioannis Gkioulekas. Prior to that, I earned my B.S. and M.S. degrees from Seoul National University, where I worked with Kyoung Mu Lee. Additionally, I worked as a research scientist at the Korea Institute of Science and Technology.

My first name is pronounced as 'Be-Young-Joo.'

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We unmute novel-view synthesis by estimating the spatial sound anywhere in a scene containing multiple unknown sound sources, by combining blind audio recordings with 3D scene information.

We introduce a method that recovers full-surround 3D reconstructions from a single kaleidoscopic image by sculpting a neural surface representation.

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.

• Area Chair, NeurIPS 2024
• Program Committee, ICCP
• Reviewer, CVPR, ICCV, ECCV, BMVC, ICLR, NeurIPS, SIGGRAPH, SIGGRAPH ASIA, TIP, TCI

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