3 papers
cs.CV2026
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…
cs.CV2026
FastSHADE: Fast Self-augmented Hierarchical Asymmetric Denoising for Efficient inference on mobile devices
Nikolay Falaleev
Real-time image denoising is essential for modern mobile photography but remains challenging due to the strict latency and power constraints of edge devices. This paper presents Fa…
eess.IV2025
DIFFRACT: Diffusion-based Restoration via Adaptive Control and Thresholding for Diffraction Imaging
Nikolay Falaleev, Nikolai Orlov
This paper presents a novel approach for denoising Electron Backscatter Diffraction (EBSD) patterns using diffusion models. We propose a two-stage training process with a UNet-base…