13 citations · 47 across the 35 of their papers we have counts for
6 papers · 1 filter
Prominence-Aware Artifact Detection and Dataset for Image Super-Resolution
Ivan Molodetskikh, Kirill Malyshev, Mark Mirgaleev +3
Generative single-image super-resolution (SISR) is advancing rapidly, yet even state-of-the-art models produce visual artifacts: unnatural patterns and texture distortions that deg…
FS-IQA: Certified Feature Smoothing for Robust Image Quality Assessment
Ekaterina Shumitskaya, Dmitriy Vatolin, Anastasia Antsiferova
We propose a novel certified defense method for Image Quality Assessment (IQA) models based on randomized smoothing with noise applied in the feature space rather than the input sp…
LEHA-CVQAD: Dataset To Enable Generalized Video Quality Assessment of Compression Artifacts
Aleksandr Gushchin, Maksim Smirnov, Dmitriy Vatolin +1
We propose the LEHA-CVQAD (Large-scale Enriched Human-Annotated Compressed Video Quality Assessment) dataset, which comprises 6,240 clips for compression-oriented video quality ass…
MEMFOF: High-Resolution Training for Memory-Efficient Multi-Frame Optical Flow Estimation
Vladislav Bargatin, Egor Chistov, Alexander Yakovenko +1
Recent advances in optical flow estimation have prioritized accuracy at the cost of growing GPU memory consumption, particularly for high-resolution (FullHD) inputs. We introduce M…
Robustness as Architecture: Designing IQA Models to Withstand Adversarial Perturbations
Igor Meleshin, Anna Chistyakova, Anastasia Antsiferova +1
Image Quality Assessment (IQA) models are increasingly relied upon to evaluate image quality in real-world systems -- from compression and enhancement to generation and streaming.…
NIC-RobustBench: A Comprehensive Open-Source Toolkit for Neural Image Compression and Robustness Analysis
Georgii Bychkov, Khaled Abud, Egor Kovalev +4
Neural image compression (NIC) is increasingly used in computer vision pipelines, as learning-based models are able to surpass traditional algorithms in compression efficiency. How…