13 citations · 47 across the 35 of their papers we have counts for
44 papers
MSU Team at the Explainable Deepfake Detection Challenge 2026: Grounded Artifact Evidence for Deepfake Detection
Artem Filippov, Aleksandr Gushchin, Kirill Koltsov +2
Recent advances in generative image models have made many manipulated images highly realistic, raising the need for detectors that are not only accurate but also able to provide vi…
DISRQAD: Diffusion Image Super-Resolution Quality Assessment Dataset and Benchmark
Nikita Kukuzei, Artem Borisov, Evgeney Bogatyrev +3
Diffusion-based image super-resolution (SR) can create visually plausible detail that is not supported by the low-resolution input. We introduce DISRQAD, a subjective-quality datas…
VCR-Bench: A Modular Open-Source Benchmark for Video Classification Robustness
Maksim Plinskiy, Aleksandr Gushchin, Sergey Lavrushkin +2
Robustness of image classification has several benchmarks, but their video counterparts are absent. In video classification temporal dimension introduces additional degrees of free…
TSRN-RTVD: Real-Time Video Deblurring System
Nikita Alutis, Danila Evsyukov, Egor Chistov +3
As video capture moves to handheld and edge devices, motion blur from camera shake has become a pervasive degradation that lowers perceptual quality and harms downstream vision tas…
Exploring Weaknesses of Generative Image Watermarks against Latent Frequency Masking
Kirill Aistov, Khaled Abud, Irina Serzhenko +8
Invisible watermarking has become a central tool for tracing AI-generated images, but its robustness against adaptive removal attacks remains an open security question. We introduc…
WARP: A Unified Benchmark for Invisible Image Watermarking -- Robustness and Protection Against Attacks
Khaled Abud, Aleksey Yakushev, Aleksandr Akimenkov +9
Digital image watermarking is increasingly critical in media contexts, as emerging regulations and industry practices require marking AI-generated content and ensuring traceable so…