13 papers
SR-Ground: Image Quality Grounding for Super-Resolved Content
Artem Borisov, Evgeney Bogatyrev, Khaled Abud +1
Super-Resolution (SR) has advanced rapidly in recent years, with diffusion-based models achieving unprecedented fidelity at the cost of introducing new types of visual artifacts. W…
SR-Prominence: A Crowdsourced Protocol and Dataset Suite for Perceptually-Weighted Super-Resolution Artifact Evaluation
Ivan Molodetskikh, Kirill Malyshev, Mark Mirgaleev +3
Modern image super-resolution methods generate detailed, visually appealing results, but they often introduce visual artifacts: unnatural patterns and texture distortions that degr…
TIQA: Human-Aligned Perceptual Text Quality Assessment in Generated Images
Kirill Koltsov, Aleksandr Gushchin, Anastasia Antsiferova +1
Recent text-to-image models have improved global realism, but text rendering remains a persistent failure mode: images may look convincing overall, yet local typography often conta…
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…
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…
Guardians of Image Quality: Benchmarking Defenses Against Adversarial Attacks on Image Quality Metrics
Alexander Gushchin, Khaled Abud, Georgii Bychkov +7
In the field of Image Quality Assessment (IQA), the adversarial robustness of the metrics poses a critical concern. This paper presents a comprehensive benchmarking study of variou…