{"ID":2853095,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.16752","arxiv_id":"2510.16752","title":"Prominence-Aware Artifact Detection and Dataset for Image Super-Resolution","abstract":"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 degrade perceived quality. These defects vary widely in perceptual impact--some are barely noticeable, while others are highly disturbing--yet existing detection methods treat them equally. We propose characterizing artifacts by their prominence to human observers rather than as uniform binary defects. We present a novel dataset of 1302 artifact examples from 11 SISR methods annotated with crowdsourced prominence scores, and provide prominence annotations for 593 existing artifacts from the DeSRA dataset, revealing that 48% of them go unnoticed by most viewers. Building on this data, we train a lightweight regressor that produces spatial prominence heatmaps. We demonstrate that our method outperforms existing detectors and effectively guides SR model fine-tuning for artifact suppression. Our dataset and code are available at https://tinyurl.com/2u9zxtyh.","short_abstract":"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 degrade perceived quality. These defects vary widely in perceptual impact--some are barely noticeable, while others are highly disturbing--yet...","url_abs":"https://arxiv.org/abs/2510.16752","url_pdf":"https://arxiv.org/pdf/2510.16752v2","authors":"[\"Ivan Molodetskikh\",\"Kirill Malyshev\",\"Mark Mirgaleev\",\"Nikita Zagainov\",\"Evgeney Bogatyrev\",\"Dmitriy Vatolin\"]","published":"2025-10-19T08:28:53Z","proceeding":"cs.CV","tasks":"[\"cs.CV\",\"cs.LG\"]","methods":"[]","project_urls":"[\"https://tinyurl.com/2u9zxtyh\"]","has_code":false}