{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/efficient-deep-models-for-real-time-4k-image","title":"Efficient Deep Models for Real-Time 4K Image Super-Resolution. NTIRE 2023 Benchmark and Report","arxiv_id":null,"date":"2023-06-01","proceeding":"CVPRW 2023 6","authors":["Marcos V. Conde","Eduard Zamfir","Radu Timofte","Daniel Motilla","and others"],"abstract":"This paper introduces a novel benchmark for efficient upscaling as part of the NTIRE 2023 Real-Time Image Super-Resolution (RTSR) Challenge, which aimed to upscale images from 720p and 1080p resolution to native 4K (x2 and x3 factors) in real-time on commercial GPUs. For this, we use a new test set containing diverse 4K images ranging from digital art to gaming and photography. We assessed the methods devised for 4K SR by measuring their runtime, parameters, and FLOPs, while ensuring a minimum PSNR fidelity over Bicubic interpolation. Out of the 170 participants, 25 teams contributed to this report, making it the most comprehensive benchmark to date and showcasing the latest advancements in real-time SR.","url_abs":"https://openaccess.thecvf.com/content/CVPR2023W/NTIRE/html/Conde_Efficient_Deep_Models_for_Real-Time_4K_Image_Super-Resolution._NTIRE_2023_CVPRW_2023_paper.html","url_pdf":"https://openaccess.thecvf.com/content/CVPR2023W/NTIRE/papers/Conde_Efficient_Deep_Models_for_Real-Time_4K_Image_Super-Resolution._NTIRE_2023_CVPRW_2023_paper.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"efficient-deep-models-for-real-time-4k-image","repo_url":"https://github.com/eduardzamfir/ntire23-rtsr","is_official":0,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":{"status":"ok","spdx":"Apache-2.0"}}],"tasks":[{"task_slug":"4k","task_name":"4k"},{"task_slug":"image-super-resolution","task_name":"Image Super-Resolution"},{"task_slug":"super-resolution","task_name":"Super-Resolution"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}