Results 21 to 30 of about 1,135,244 (321)
SeeSR: Towards Semantics-Aware Real-World Image Super-Resolution [PDF]
Computer Vision and Pattern Recognition, 2023 Owe to the powerful generative priors, the pretrained text-to-image (T2I) diffusion models have become increasingly popular in solving the real-world image super-resolution problem.
Rongyuan Wu +5 more
semanticscholar +1 more source
Image Super-Resolution Using Deep Convolutional Networks [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2014 We propose a deep learning method for single image super-resolution (SR). Our method directly learns an end-to-end mapping between the low/high-resolution images.
Chao Dong +3 more
semanticscholar +1 more source
Pixel-Aware Stable Diffusion for Realistic Image Super-resolution and Personalized Stylization [PDF]
European Conference on Computer Vision, 2023 Diffusion models have demonstrated impressive performance in various image generation, editing, enhancement and translation tasks. In particular, the pre-trained text-to-image stable diffusion models provide a potential solution to the challenging ...
Tao Yang +3 more
semanticscholar +1 more source
SUPER-RESOLUTION OF MULTISPECTRAL IMAGES [PDF]
Modelling and Simulation in Science, 2007 In this paper we propose and analyze a globally and locally adaptive super-resolution Bayesian methodology for pansharpening of multispectral images. The methodology incorporates prior knowledge on the expected characteristics of the multispectral images uses the sensor characteristics to model the observation process of both panchromatic and ...
Miguel Vega +3 more
openaire +1 more source
Hyperspectral Image Super-Resolution with RGB Image Super-Resolution as an Auxiliary Task [PDF]
2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2022 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
Li, Ke, Dai, Dengxin, van Gool, Luc
openaire +4 more sources
Residual Dense Network for Image Super-Resolution [PDF]
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018 A very deep convolutional neural network (CNN) has recently achieved great success for image super-resolution (SR) and offered hierarchical features as well.
Yulun Zhang +4 more
semanticscholar +1 more source
Accurate Image Super-Resolution Using Very Deep Convolutional Networks [PDF]
Computer Vision and Pattern Recognition, 2015 We present a highly accurate single-image superresolution (SR) method. Our method uses a very deep convolutional network inspired by VGG-net used for ImageNet classification [19].
Jiwon Kim, Jung Kwon Lee, Kyoung Mu Lee
semanticscholar +1 more source
Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network [PDF]
Computer Vision and Pattern Recognition, 2016 Recently, several models based on deep neural networks have achieved great success in terms of both reconstruction accuracy and computational performance for single image super-resolution. In these methods, the low resolution (LR) input image is upscaled
Wenzhe Shi +7 more
semanticscholar +1 more source
SinSR: Diffusion-Based Image Super-Resolution in a Single Step [PDF]
Computer Vision and Pattern Recognition, 2023 While super-resolution (SR) methods based on diffusion models exhibit promising results, their practical application is hindered by the substantial number of required inference steps.
Yufei Wang +9 more
semanticscholar +1 more source
CoRR, 2021 This study presents a chronological overview of the single image super-resolution problem. We first define the problem thoroughly and mention some of the serious challenges. Then the problem formulation and the performance metrics are defined. We give an overview of the previous methods relying on reconstruction based solutions and then continue with ...
Baran Ataman, Mert Seker, David McKee
openaire +2 more sources