activity
20202023
most citedSemi-Supervised Raw-to-Raw Mapping

3 citations · 4 across the 7 of their papers we have counts for

collaborators

9 papers

cs.CV2023

: Dual-Camera Defocus Control by Learning to Refocus

Hadi Alzayer, Abdullah Abuolaim, Leung Chun Chan +4

Smartphone cameras today are increasingly approaching the versatility and quality of professional cameras through a combination of hardware and software advancements. However, fixe…

cs.CV2022★ 1 cited

Day-to-Night Image Synthesis for Training Nighttime Neural ISPs

Abhijith Punnappurath, Abdullah Abuolaim, Abdelrahman Abdelhamed +2

Many flagship smartphone cameras now use a dedicated neural image signal processor (ISP) to render noisy raw sensor images to the final processed output. Training nightmode ISP net…

cs.CV2021

Multi-View Motion Synthesis via Applying Rotated Dual-Pixel Blur Kernels

Abdullah Abuolaim, Mahmoud Afifi, Michael S. Brown

Portrait mode is widely available on smartphone cameras to provide an enhanced photographic experience. One of the primary effects applied to images captured in portrait mode is a…

cs.CV2021

Improving Single-Image Defocus Deblurring: How Dual-Pixel Images Help Through Multi-Task Learning

Abdullah Abuolaim, Mahmoud Afifi, Michael S. Brown

Many camera sensors use a dual-pixel (DP) design that operates as a rudimentary light field providing two sub-aperture views of a scene in a single capture. The DP sensor was devel…

cs.CV2021

CAMS: Color-Aware Multi-Style Transfer

Mahmoud Afifi, Abdullah Abuolaim, Mostafa Hussien +2

Image style transfer aims to manipulate the appearance of a source image, or "content" image, to share similar texture and colors of a target "style" image. Ideally, the style tran…

cs.CV2021★ 3 cited

Semi-Supervised Raw-to-Raw Mapping

Mahmoud Afifi, Abdullah Abuolaim

The raw-RGB colors of a camera sensor vary due to the spectral sensitivity differences across different sensor makes and models. This paper focuses on the task of mapping between d…

eess.IV2020

Learning to Reduce Defocus Blur by Realistically Modeling Dual-Pixel Data

Abdullah Abuolaim, Mauricio Delbracio, Damien Kelly +2

Recent work has shown impressive results on data-driven defocus deblurring using the two-image views available on modern dual-pixel (DP) sensors. One significant challenge in this…

cs.CV2020

CIE XYZ Net: Unprocessing Images for Low-Level Computer Vision Tasks

Mahmoud Afifi, Abdelrahman Abdelhamed, Abdullah Abuolaim +2

Cameras currently allow access to two image states: (i) a minimally processed linear raw-RGB image state (i.e., raw sensor data) or (ii) a highly-processed nonlinear image state (e…

eess.IV2020

Defocus Deblurring Using Dual-Pixel Data

Abdullah Abuolaim, Michael S. Brown

Defocus blur arises in images that are captured with a shallow depth of field due to the use of a wide aperture. Correcting defocus blur is challenging because the blur is spatiall…