63 datasets found

Single image super-resolution (SR) is the process of infer-

Large scale image super-resolution is a challenging computer vision task, since vast information is missing in a highly degraded image.

The Ntire 2017 challenge on single image super-resolution: Methods and results.

The dataset used in the design of a practical degradation model for deep blind image super-resolution.

The dataset used for testing the proposed Multi-scale Dense Cross Network (MDCN) for image super-resolution.

The RFL dataset contains 291 images.

The proposed DRFN for large-scale accurate SISR. The dataset used for training and testing is RFL, VDSR, and Berkeley Segmentation Dataset.

The dataset used for training and testing the real-world image super-resolution algorithm.

The dataset used for training and testing the proposed dSRVAE model for real-world image super-resolution.

The div2k dataset contains 1000 2K-resolution images for single-image super-resolution.

Advanced diffusion models perform impressively in image super-resolution, but the high memory and computational costs hinder their deployment. Binarization, an ultra-compression...

Change Detection (CD) is an important problem in remote sensing in which our goal is to identify relevant changes in bi-temporal remote sensing images that can help in various...

The dataset used in the paper is a synthetic dataset for blind super-resolution, consisting of low-resolution images and their corresponding blur kernels.

The dataset used in this paper is a collection of convolutional neural network (CNN) weights, which are compressed using transform quantization.

The CelebAHQ dataset was used with a box-downsampling operator [11].

LSUN Tower dataset is a subset of the LSUN dataset, with 708,264 images.

LSUN Dining Room dataset is a subset of the LSUN dataset, with 657,571 images.

A large-scale dataset of multi-view images for 3D scene understanding.

The proposed HPAN model uses pixel attention for better image quality than FSRCNN but keeps the structure simple for small model size and low complexity.

The dataset consists of 100 images with varying sizes.