1 citations · 1 across the 6 of their papers we have counts for
10 papers
RGB Photo Enhancement with Deep Learning on Smartphone GPUs: Mobile AI 2026 Challenge Report
Andrey Ignatov, Georgy Perevozchikov, Radu Timofte +21
On-device RGB photo enhancement is a popular task that is needed for quality improvement of photos captured with mobile devices as well as for retouching of images acquired through…
Learned Smartphone ISP on Mobile GPUs: Mobile AI 2026 Challenge Report
Andrey Ignatov, Georgy Perevozchikov, Radu Timofte +19
With the increasing importance of mobile camera quality in modern smartphones, growing attention has been directed toward computational photography and advanced image signal proces…
Efficient Image Denoising on Smartphone GPUs: Mobile AI 2026 Challenge Report
Andrey Ignatov, Georgy Perevozchikov, Radu Timofte +17
Image denoising is a fundamental problem in mobile photography. Despite a large number of solutions proposed for this task, the majority of them are trained on synthetically produc…
4K Image Super-Resolution on Mobile NPUs: Mobile AI 2026 Challenge Report
Andrey Ignatov, Georgy Perevozchikov, Radu Timofte +43
Image super-resolution is widely used on mobile devices for upscaling various types of image data. This creates a need for efficient deep learning-based models that are not only pe…
NTIRE 2026 Low-light Enhancement: Twilight Cowboy Challenge
Aleksei Khalin, Egor Ershov, Artyom Panshin +46
This paper presents a review of the NTIRE 2026 Low-light Enhancement: Twilight Cowboy Challenge. The objective of the competition was to merge a set of misaligned smartphone images…
Experts-Guided Unbalanced Optimal Transport for ISP Learning from Unpaired and/or Paired Data
Georgy Perevozchikov, Nancy Mehta, Egor Ershov +1
Learned Image Signal Processing (ISP) pipelines offer powerful end-to-end performance but are critically dependent on large-scale paired raw-to-sRGB datasets. This reliance on cost…
Modulate and Reconstruct: Learning Hyperspectral Imaging from Misaligned Smartphone Views
Daniil Reutsky, Daniil Vladimirov, Yasin Mamedov +4
Hyperspectral reconstruction (HSR) from RGB images is a highly promising direction for accurate color reproduction and material color measurement. While most existing approaches re…
Color Matching Using Hypernetwork-Based Kolmogorov-Arnold Networks
Artem Nikonorov, Georgy Perevozchikov, Andrei Korepanov +4
We present cmKAN, a versatile framework for color matching. Given an input image with colors from a source color distribution, our method effectively and accurately maps these colo…
Rawformer: Unpaired Raw-to-Raw Translation for Learnable Camera ISPs
Georgy Perevozchikov, Nancy Mehta, Mahmoud Afifi +1
Modern smartphone camera quality heavily relies on the image signal processor (ISP) to enhance captured raw images, utilizing carefully designed modules to produce final output ima…
Learned Smartphone ISP on Mobile GPUs with Deep Learning, Mobile AI & AIM 2022 Challenge: Report
Andrey Ignatov, Radu Timofte, Shuai Liu +35
The role of mobile cameras increased dramatically over the past few years, leading to more and more research in automatic image quality enhancement and RAW photo processing. In thi…