In recent years, real image super-resolution (SR) has achieved The first benchmark dataset featuring high-resolution SR methods, including data from fluid flows, cosmology, and weather is introduced, with the aim of validating spatial SR performance from data-centric and physics-preserved perspectives, as well as assessing robustness to data degradation tasks. 00474 Corpus ID: 237498263; Real-world Video Super-resolution: A Benchmark Dataset and A Decomposition based Learning Scheme @article{Yang2021RealworldVS, title={Real-world Video Super-resolution: A Benchmark Dataset and A Decomposition based Learning Scheme}, author={Xi Yang and Wangmeng Xiang and Huiyu Zeng and Lei Zhang}, journal={2021 IEEE/CVF International Jun 24, 2023 · introduce. g. 2048. Furthermore Oct 1, 2021 · DOI: 10. Extensive experiments on existing public datasets demonstrate the effectiveness and efficiency of our network compared with the state-of-the-art methods. Super-resolution imaging ( SR) is a class of techniques that enhance (increase) the resolution of an imaging system. May 8, 2023 · Abstract —We developed a super-resolution (SR) benchmark to. VFHQ: A High-Quality Dataset and Benchmark for Video Face Super Resolution Liangbin Xie 1,2,3 , Xintao Wang 3 , Honglun Zhang 3 , Chao Dong 1* , Ying Shan 3 1 Shenzhen Key Lab of Computer Vision and Pattern Recognition, Single-Image Super-Resolution: A Benchmark Chih-Yuan Yang 1, Chao Ma12, and Ming-Hsuan Yang 1University of California at Merced 2Shanghai Jiao Tong University fcyang35, cma26, mhyangg@ucmerced. 42. See a full comparison of 48 papers with code. New metrics for detail restoration quality. For fixed-arithmetic quantization of image super resolution. yue, zmzhang, yjy}@tju. Edit. Jianrui Cai, Hui Zeng, Hongwei Yong, Zisheng Cao, Lei Zhang. Our benchmark determines the best upscaling methods for increasing video resolution and improving visual quality using our compact yet comprehensive dataset. Single-image super-resolution is of great importance for vi-sion applications, and numerous algorithms have been proposed in recent years. Most of the existing learning-based single image superresolution (SISR) methods are trained and evaluated on simulated datasets, where the low-resolution (LR) images are generated by applying a simple A collection of codes and datasets for light field super-resolution methods evaluated in the following paper Zhen Cheng, Zhiwei Xiong, Chang Chen, Dong Liu. The dataset for the benchmark was collected using video codecs of 5 different compression E cient and Accurate Quantized Image Super-Resolution on Mobile NPUs 3 bile AI acceleration hardware, its particularities and performance. 1 driver, and we've been testing it for the past few days. TLDR. 2048 ×. 0 is AMD's second attempt at offering a broad game upscaling technology to compete with Nvidia's DLSS. Local-Global Fusion Network for Video Super-Resolution. Light Field Super-Resolution: A Benchmark. By Anil Chandra Naidu Matcha. com Besides, we provide a fast depth map super-resolution (FDSR) baseline, in which the high-frequency component adaptively decomposed from RGB image to guide the depth map SR. Hailed as Team Red's Introduction. Here is presented a sample code for performing benchmarking, and then a few benchmarking results are collected. In this paper, we introduce a new benchmark (named MuS2) for super-resolving multiple Sentinel-2 images, with WorldView-2 imagery used as the high Apr 13, 2021 · DOI: 10. However, limited by the lack of real-world paired low-resolution (LR) and HR depth maps, most existing methods use @inproceedings{cai2019toward, title={Toward real-world single image super-resolution: A new benchmark and a new model}, author={Cai, Jianrui and Zeng, Hui and Yong, Hongwei and Cao, Zisheng and Zhang, Lei}, booktitle={Proceedings of the IEEE International Conference on Computer Vision}, year={2019} } The RGB-D-D (RGB-depth-depth) dataset contains 4811 paired samples ranging from indoor scenes to challenging outdoor scenes. Despite substantial advances, single-image super-resolution (SISR) is always in a dilemma to reconstruct high-quality images with limited information from one input image, especially in realistic scenarios. RealBSR: A new Benchmark. This work formulate light field super-resolution (LFSR) as tensor restoration and develop a learning framework based on a two-stage restoration with 4-dimensional (4D) convolution, which allows the model to learn the features capturing the geometry information encoded in multiple adjacent views. 2023 [Video Saliency Prediction Benchmark] Release of the benchmark ; 21. LapSRN ; Deep Laplacian Pyramid Networks for Fast and Accurate Super-Resolution (CVPR 2017), Wei-Sheng Lai et al. 3. The current state-of-the-art on MSU Video Upscalers: Quality Enhancement is BSRGAN. Our dataset. Thus, depth map super-resolution (SR) is a practical and valuable task, which upscales the depth map into high-resolution (HR) space. - pf0607/COZ Mar 1, 2023 · This work aims to promote the application of a high-performance super-resolution (SR) method in industry. To explore their performance on UHD images, in this paper, we first introduce two large-scale image datasets, UHDSR4K and UHDSR8K, to benchmark existing SISR Elevate Performance Across Thousands of Games. Vega 64 is the next AMD GPU we have for testing, using a prior Jan 1, 2022 · We developed a super-resolution (SR) benchmark to analyze SR capabilities to upscale compressed videos. Basicvsr: The search for essential components in video super-resolution and beyond. All of these scores were obtained from pairwise comparisons of different distorted videos with a single reference video (ground-truth, GT). the super-resolution domain for an extended period. Abstract. Explore a platform that offers the freedom to write and express oneself on various topics. 79. Single-image super-resolution is of great importance for vision applications, and numerous algorithms have been proposed in recent years. Sep 21, 2023 · In this paper, we introduce a new benchmark (named MuS2) for super-resolving multiple Sentinel-2 images, with WorldView-2 imagery used as the high-resolution reference. 2) low-level vision: real-world image Super-Resolution (e. dimensions), including data from fluid flows, cosmology, and weather. Image Super Resolution refers to the task of enhancing the resolution of an image from low-resolution (LR) to high (HR). The input images can be large patches or full-resolution images, compressed using JPEG q=90. 136 papers with code • 15 benchmarks • 15 datasets. 5. You can also send us the code of your method or the executable file and we will run it ourselves. 2. 2023 [Super-Resolution Quality Metrics Benchmark] Release of the benchmark ; 20. Description. msu. However, limited by the lack of real-world paired low-resolution (LR) and HR depth maps, most existing methods use Despite substantial advances, single-image super-resolution (SISR) is always in a dilemma to reconstruct high-quality images with limited information from one input image, especially in realistic scenarios. 6. Feb 28, 2023 · To enable it, launch the NVIDIA Control Panel and open “Adjust video image settings. Hyperspectral image super-resolution is a kind of technique that can generate a high spatial and high spectral resolution image from one of the following observed data (1) low-resolution multispectral image, e. In optical SR the diffraction limit of systems is transcended, while in geometrical SR the resolution of digital imaging sensors is enhanced. Thus, depth map super-resolution (SR) is a practical and valuable task, which up-scales the depth map into high-resolution (HR) space. Citation @inproceedings { zhang2021edge , title = { Edge-oriented Convolution Block for Real-time Super Resolution on Mobile Devices } , author = { Zhang, Xindong and Zeng, Hui and Zhang, Lei } , booktitle = { Proceedings of the 29th ACM International Conference on Multimedia Jun 1, 2019 · 2021. Those still on Radeon Vega or RX 500 "Polaris" are out of luck. Check Video Super Resolution models’ ability to restore real details; The most complex content for restoration task: faces, text, QR-codes, car numbers, unpatterned textures, small details See plots and visualizations for particular content types Jun 24, 2023 · To address this, we introduce SuperBench, the first benchmark dataset featuring high-resolution datasets (up to 2048 × 2048 dimensions), including data from fluid flows, cosmology, and weather. , advertising posters, plants, offices, buildings. Super-Resolution (SR) techniques aim to enhance data resolution, enabling the retrieval of finer details, and improving the overall quality and fidelity of the data representation. SuperBench is a benchmark dataset and evaluation framework for super-resolution (SR) tasks in scientific domains. The "D-D" means the paired LR and HR depth maps captured from the mobile phone (LR sensors) and Lucid Helios (HR sensors), respectively. 264, H. This sample demonstrates the DirectML API by implementing a super-resolution machine learning (ML) model on the GPU. 02 OS. 1, our benchmark system is in a three-level architecture, which includes a web Oct 1, 2021 · We developed a super-resolution (SR) benchmark to analyze SR capabilities to upscale compressed videos. As shown in these works, the latest generations of mobile NPUs are reaching the performance of older-generation mid-range desktop GPUs. 1109/ICCV48922. 266, AV1, and AVS3. In this paper, we establish a large-scale real-world burst super-resolution dataset, i. This rating is based on the correlation between the values of metrics with subjective scores. In your NVIDIA Control Panel, under Adjust Video Image Settings -> RTX video enhancements, enable Super Resolution or HDR. Our benchmark is aimed to find the best algorithms for the restoration of real details during Video Super Resolution processing. There is growing interest in applying SR methods to complex spatiotemporal systems Acclerating the Super-Resolution Convolutional Neural Network (ECCV2016), Dong Chao et al. These strategies largely leverage techniques such as residual learn-ing [12,36,46,52,61], or recursive learning [18,21] for de-veloping network architectures, significantly propelling the progress of super-resolution models forward. This survey is an effort to provide a detailed 1364 papers with code • 1 benchmarks • 21 datasets. Within MuS2, we publish the Super-Resolution. Expand. Enter. , LR RGB image, (2) high-resolution multispectral image, e. The goal is to produce an output image with a higher resolution than the input image, while preserving the See full list on github. Sep 21, 2023 · One of the obstacles in multi-image super-resolution consists in the scarcity of real-world benchmarks-commonly, simulated data are exploited which do not fully reflect the operating conditions. The purpose of a Rayleigh task is to see how signal length and super-resolution network complexity impact on s binary detection performance. Official dataset and codes of Continuous Optical Zooming: A Benchmark for Arbitrary-Scale Image Super-Resolution in Real World[CVPR2024]. The text region pairs contained 33,789 text lines, among which 24,666 were Chinese texts with complex structures. As shown in Fig. To this end, a substantial amount of efforts have been dedicated to light field super-resolution (SR) in recent years. In this paper, we present a systematic benchmark evaluation May 8, 2023 · We developed a super-resolution (SR) benchmark to analyze SR's capacity to upscale compressed videos. 1109/CVPR46437. May 16, 2024 · 1. 265, H. Apply your algorithm. It provides high-quality datasets and baseline models for evaluating and comparing SR methods in various scientific applications. , RealBSR, is established to explore the faithful reconstruction of image details from multiple frames and a Federated Burst Affinity network (FBAnet) is introduced to investigate non-trivial pixel-wise displacements among images under real- world image degradation. , bicubic downsampling) at continuous various scales, thereby falling short in capturing the complex degradation of real-world images. Video super-resolution (VSR) aims to improve the spatial resolution of low-resolution (LR) videos. Despite the demonstrated success, these results are often generated based on different assumptions using different datasets and metrics. Despite the demonstrated success, existing light field SR methods are often evaluated based on Super-Resolution with a Benchmark Dataset Huanjing Yue , Zhiming Zhang , and Jingyu Yang⋆ School of Electrical and Information Engineering, Tianjin University, Tianjin, China {huanjing. In this article we'll be using the game Deathloop which Jun 17, 2019 · Lenslet-based light field imaging generally suffers from a fundamental trade-off between spatial and angular resolutions, which limits its promotion to practical applications. Our benchmark provides a ranking of Super-Resolution quality evaluation metrics. The end result is a high-resolution version of the original image. In this work, we extend the powerful ESRGAN to a practical Nov 15, 2021 · Restore high-resolution frames with your algorithm. 264 May 12, 2023 · Added link to Metrics Robustness Benchmark. Contacts #2 best model for Video Super-Resolution on MSU Video Super Resolution Benchmark: Detail Restoration (Subjective score metric) Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network. edu Abstract. 07. AMD FidelityFX™ Super Resolution (FSR) 1 uses cutting-edge open upscaling and advanced frame generation technologies to help boost your frame rates in supported games 2 and deliver amazing high-quality, high-performance gaming on virtually any hardware. DRealSR establishes a Super Resolution (SR) benchmark with diverse real-world degradation processes, mitigating the limitations of conventional simulated image degradation. May 10, 2021 · Key features of the Benchmark. Video Super-Resolution is a computer vision task that aims to increase the resolution of a video sequence, typically from lower to higher resolutions. In this paper, we introduce a new benchmark (named MuS2) for super-resolving multiple Sentinel-2 images, with WorldView-2 imagery used as the high-resolution reference. It is popularly used in the following applications: Surveillance: to detect, identify, and perform facial recognition on low-resolution images obtained from security cameras. Furthermore 663 papers with code • 61 benchmarks • 41 datasets. OBJECTIVES AND TESTING RULES. Image super-resolution (SR) is one of the vital image processing methods that improve the resolution of an image in the field of computer vision. In Proceedings of the IEEE/CVF International Conference on Computer Vision, pages 3086–3095, 2019. , bicubic downsampling). 4 days ago · The super-resolution module contains sample codes for benchmarking, in order to compare different models and algorithms. , HR RGB image or other 2D measurement, (3) low-resolution hyperspectral Blind Super-Resolution (BlindSR) aims to reconstruct high-resolution (HR) images from low-resolution (LR) images without prior knowledge of the image degradation process. Send us result. Note that we take hyperspectral image In this paper, we established a Chinese-English benchmark, namely Real-CE, for scene text image super-resolution (STISR) model training. Windows “Graphics settings”: Under Custom options for apps, add the path to your Chrome or Edge browser. Within MuS2, we publish the first end-to-end evaluation procedure for this problem which we expect to help the researchers in advancing the state of the art in multi-image super Sep 8, 2017 · The datasets cover four spatial resolution levels using camera hardware binning. 2023 [Metrics Robustness Benchmark] Beta-version release This is the official implementation of ICCV2023 "Towards Real-World Burst Image Super-Resolution: Benchmark and Method". The challenge has two tracks: Oct 6, 2022 · In this paper, we introduce a new MuS2 benchmark for super-resolving multiple Sentinel-2 images, with WorldView-2 imagery used as the high-resolution reference. Name of your method that will be specified in our benchmark. Aug 5, 2022 · Personal email: dmitriy@graphics. Apr 22, 2022 · Download low-resolution input videos as sequences of frames in PNG format. 3 benchmarks with different time distortions; 560 test pairs in each Benchmark with a total duration of ~2 million frames; Combinations of 13 frequent distortions obtained due to human/machine video editing and processing; MSU Video Super Resolution Benchmark New metrics for detail restoration Mar 17, 2022 · Radeon Super Resolution requires an AMD Radeon GPU and the latest 22. BurstSR is the only existing dataset for real-world burst image super-resolution and enhancement, which has three typical issues. You can also send us the code of your method or the executable file with the instructions on how to run it and we will run it ourselves. We assessed 17 state-ofthe-art SR models using our benchmark and evaluated their ability to preserve scene context and their susceptibility to compression artifacts. Furthermore Despite substantial advances, single-image super-resolution (SISR) is always in a dilemma to reconstruct high-quality images with limited information from one input image, especially in realistic scenarios. Moreover, we design an edge-aware learning method, which provides structural supervision in image and proving performance with a simpler model design. Existing VSR methods are mostly trained and evaluated on synthetic datasets, where the LR videos are uniformly downsampled from their high-resolution (HR) counterparts by some simple operators (e. This report presents the results of MSU Super-Resolution for Video Compression. Deep learning-based image super-resolution (SR) has shown its strong capability in recovering high-resolution image details from low-resolution inputs. The company currently supports the Radeon RX 5000 and RX 6000 series, which is RDNA and RDNA 2. The training images are cropped into 380× Abstract: Most current arbitrary-scale image super-resolution (SR) methods has commonly relied on simulated data generated by simple synthetic degradation models (e. 00911 Corpus ID: 233219880; Towards Fast and Accurate Real-World Depth Super-Resolution: Benchmark Dataset and Baseline @article{He2021TowardsFA, title={Towards Fast and Accurate Real-World Depth Super-Resolution: Benchmark Dataset and Baseline}, author={Lingzhi He and Hongguang Zhu and Feng Li and Huihui Bai and Runmin Cong and Chunjie Zhang and Chunyu Lin and Depth maps obtained by commercial depth sensors are always in low-resolution, making it difficult to be used in various computer vision tasks. This is a challenging problem in real-world applications, where the degradation can be complex and unknown. ai with the following information: A. 1) high-level vision: weakly-supervised object detection, unsupervised domain adaptation, robust object detection, adversarial attack and defense. Image Super-Resolution is a machine learning task where the goal is to increase the resolution of an image, often by a factor of 4x or more, while maintaining its content and details as much as possible. With this database, we benchmark 15 single-image and multi-frame SR algorithms. Besides, we provide a fast depth map super-resolution (FDSR) baseline, in which the high-frequency component adaptively decomposed from RGB image to guide the depth map SR. The current state-of-the-art on Set5 - 4x upscaling is DRCT-L. Feb 16, 2023 · To mitigate this gap, we develop an online benchmark to automatically evaluate the performance of SR models on mobile devices. To get an accurate . Nevertheless, a straightforward de- Depth maps obtained by commercial depth sensors are always in low-resolution, making it difficult to be used in various computer vision tasks. 3. Snapdragon GSR single pass solution is the latest first-to-market feature for mobile and XR gaming. 1. With the ubiquitous use of AI-accelerators on mobile devices (e. Here, we focus on validating spatial SR performance from data-centric and physics-preserved perspectives, as well as assessing robustness to data Jul 22, 2021 · Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data. Check the super resolution box under “RTX video enhancement” and select a quality from one to four — ranging from the lowest impact on GPU performance to the highest level of upscaling improvement. , the first benchmark dataset featuring high-resolution datasets (up to. Recent unsupervised learning-based BlindSR methods can estimate the image degradation in an unsupervised manner, but Jul 13, 2021 · Abstract. 12. Jun 1, 2019 · Download Citation | On Jun 1, 2019, Zhen Cheng and others published Light Field Super-Resolution: A Benchmark | Find, read and cite all the research you need on ResearchGate What is Snapdragon Game Super Resolution (GSR)? Snapdragon GSR is a single pass spatial aware super resolution technique developed by the Qualcomm Snapdragon Studios to achieve optimal super scaling quality at the best performance and power savings. Send us an email to vsr-benchmark@videoprocessing. EDSR ; Enhanced Deep Residual Networks for Single Image Super-Resolution (Winner of NTIRE2017 Super-Resolution Challenge), Bee Lim et al. cs. ru. Here is the (include Cropped RealBSR-RGB), the (include Full-size RealBSR-RGB) and the [google drive link] (include Cropped RealBSR-RGB and Cropped RealBSR-RAW) of the proposed RealBSR dataset. e. Apply your Super-Resolution algorithm to upscale frames to 1920×1080 resolution. See a full comparison of 6 papers with code. 04. Video Super-Resolution. The ML model performs a smart upscale of an image to double its original resolution. ”. 1 Overall Pipeline of Benchmark To ease the burden of deploying and evaluating SR models on mobile devices, we propose an autonomous and hierarchical benchmark system. We specifically asked AMD about this, and the response was that "AMD Radeon Super Get a Boost in Frames for Your Games. 1. Mar 1, 2023 · The efficiency and performance of DL-SR algorithms are evaluated quantitatively using a task-based super-resolution (SR) image quality assessment [45]. 57. [5] Kelvin CK Chan, Xintao Wang, Ke Yu, Chao Dong, and Chen Change Loy. 2023 [SR+Codecs Benchmark] Added E-MoEVRT ; 01. In recent years, real image super-resolution (SR) has achieved Sep 9, 2023 · A large-scale real-world burst super-resolution dataset, i. Evaluating Image Super-Resolution Performance on Mobile Devices 173 3. It contained 1,935 training and 783 testing images. With a simple model definition file as input, e. The goal is to generate high-resolution video frames from low-resolution input, improving the overall quality Some VSR methods may produce the wrong digit or an entirely different face. Meanwhile, we build a real-world burst image super-resolution dataset, named RealBSR, aim-ing to facilitate further exploration of real-world burst SR. 09. Radeon™ Super Resolution (RSR) is an in-driver upscaling feature that uses the same algorithm found in AMD FidelityFX™ Super Resolution (FSR) technology. Learn more, including other setup configurations Jul 27, 2021 · AMD has finally released its FidelityFX Super Resolution to the public (aka AMD FSR ), along with a new 21. 2020. Despite substantial advances, single-image super-resolution (SISR According to kind of observed data, hyperspectral image super-resolution techniques can be divided into four classes: spatiospectral super-resolution (SSSR), spectral super-resolution (SSR), single hyperspectral image super-resolution (SHSR), and multispectral image and hyperspectral image fusion (MHF). It was performed on an Intel i7-9700K CPU on an Ubuntu 18. 1366 papers with code • 1 benchmarks • 21 datasets. May 24, 2022 · FidelityFX Super Resolution 2. , PyTorch or ONNX Super-resolution imaging. In CVPRW 2019. Gamers can take advantage of Radeon™ Super Resolution technology to unleash new levels of performance on any compatible game. Click on the gear icon in the upper right Feb 28, 2024 · Toward real-world single image super-resolution: A new benchmark and a new model. Our dataset employed video codecs based on five compression standards: H. Considering the lack of industrial datasets to evaluate performance, an industrial image SR dataset called WCI110 is first established, comprising 110 typical welding component images with 2040 × 1524 pixels. This includes converting between image and tensor formats, initializing and executing ML operators, and interleaving graphics and ML work. Everyone is welcome to participate! Run your favorite super-resolution method on our compact test video and send us the result to see how well it performs. Here, we Apr 24, 2024 · Right-click on the Radeon Settings icon in the System Tray and select AMD Radeon Software (or right-click on the desktop and select it from the menu). The RGB-D-D can not only meet the real scenes and real correspondences for depth map Jun 22, 2021 · The 5700 XT also benefits more at 1440p than the 6800 XT, with a 29% uplift going from native rendering to FSR Ultra Quality. SuperBench. In the last two decades, significant progress has been made in the field of super-resolution, especially by utilizing deep learning methods. Benchmark, in Jun 1, 2021 · Request PDF | On Jun 1, 2021, Lingzhi He and others published Towards Fast and Accurate Real-World Depth Super-Resolution: Benchmark Dataset and Baseline | Find, read and cite all the research you Jun 24, 2023 · SuperBench: A Super-Resolution Benchmark Dataset for Scientific Machine Learning. Though many attempts have been made in blind super-resolution to restore low-resolution images with unknown and complex degradations, they are still far from addressing general real-world degraded images. An overview of super-resolution for weather data. employed video codecs based on five compression standards: H. , real-world SR benchmarks, single image real-world SR, unsupervised domain adaptation real-world SR, robust real-world SR). Super-Resolution (SR) techniques aim to enhance data resolution, enabling the retrieval of finer The benchmark provides 1,935/783 real-world LR-HR text image pairs~ (contains 33,789 text lines in total) for training/testing in 2 × and 4 × zooming modes, complemented by detailed annotations, including detection boxes and text transcripts. 2016. Because of the complicated and Jun 23, 2024 · For our latest GPU benchmarks, we've tested nearly every GPU released in the past seven years, plus some extras, at 1080p medium and 1080p ultra, and sorted the table by the 1080p ultra results. 05. cn Abstract. Subjects: Super-Resolution with a Benchmark Dataset Huanjing Yue, Zhiming Zhang, and Jingyu Yang⋆ School of Electrical and Information Engineering, Tianjin University, Tianjin, China {huanjing. , smartphones), increasing attention has been received to develop mobile-friendly SR models. Oct 1, 2023 · Download Citation | On Oct 1, 2023, Pengxu Wei and others published Towards Real-World Burst Image Super-Resolution: Benchmark and Method | Find, read and cite all the research you need on Apr 1, 2019 · Toward Real-World Single Image Super-Resolution: A New Benchmark and A New Model. Such simple synthetic degradation models, however, cannot well describe 27. Super-Resolution is a task in computer vision that involves increasing the resolution of an image or video by generating missing high-frequency details from low-resolution input. 1 drivers being released today. Whether a method’s results are trustworthy depends on how well it restores truthful details. 2021. However, current single image super-resolution (SISR) methods focus on super-resolving images to ones with resolution up to high definition (HD) and ignore higher-resolution UHD images. , RealBSR, to explore the faithful reconstruction of image details from multiple frames. Send us result to sr-codecs-benchmark@videoprocessing. analyze SR’s capacity to upscale compressed videos. ai; If you would like to participate, read the full submission rules here. edu. The dataset for the benchmark was collected using video codecs of 5 different compression Aug 31, 2021 · 2. For example, it can scale a 540p image to 1080p. Our experiments quantitatively analyze SR accuracy and robustness under realistic conditions including independent object and camera motion or photometric variations. The goal is to produce an output image with a higher resolution than the input image, while The goal of the NTIRE 2023 Real-Time Super-Resolution Challenge is to upscale images in real-time at 30-60FPS using deep learning models and commercial GPUs (RTX 3060, 3090). It has been collected from five DSLR cameras in natural scenes and cover indoor and outdoor scenes avoiding moving objects, e. ub ff or xl uz pl tt de iu jj