Blind image super-resolution: A survey and beyond
Blind image super-resolution (SR), aiming to super-resolve low-resolution images with
unknown degradation, has attracted increasing attention due to its significance in promoting …
unknown degradation, has attracted increasing attention due to its significance in promoting …
Reference-based image super-resolution with deformable attention transformer
Reference-based image super-resolution (RefSR) aims to exploit auxiliary reference (Ref)
images to super-resolve low-resolution (LR) images. Recently, RefSR has been attracting …
images to super-resolve low-resolution (LR) images. Recently, RefSR has been attracting …
Refsr-nerf: Towards high fidelity and super resolution view synthesis
Abstract We present Reference-guided Super-Resolution Neural Radiance Field (RefSR-
NeRF) that extends NeRF to super resolution and photorealistic novel view synthesis …
NeRF) that extends NeRF to super resolution and photorealistic novel view synthesis …
Deep learning in medical image super resolution: a review
H Yang, Z Wang, X Liu, C Li, J Xin, Z Wang - Applied Intelligence, 2023 - Springer
Super-resolution (SR) reconstruction is a hot topic in medical image processing. SR implies
reconstructing corresponding high-resolution (HR) images from observed low-resolution …
reconstructing corresponding high-resolution (HR) images from observed low-resolution …
Transformer-empowered multi-scale contextual matching and aggregation for multi-contrast MRI super-resolution
Magnetic resonance imaging (MRI) can present multi-contrast images of the same
anatomical structures, enabling multi-contrast super-resolution (SR) techniques. Compared …
anatomical structures, enabling multi-contrast super-resolution (SR) techniques. Compared …
Hqg-net: Unpaired medical image enhancement with high-quality guidance
Unpaired medical image enhancement (UMIE) aims to transform a low-quality (LQ) medical
image into a high-quality (HQ) one without relying on paired images for training. While most …
image into a high-quality (HQ) one without relying on paired images for training. While most …
Dynast: Dynamic sparse transformer for exemplar-guided image generation
One key challenge of exemplar-guided image generation lies in establishing fine-grained
correspondences between input and guided images. Prior approaches, despite the …
correspondences between input and guided images. Prior approaches, despite the …
Any-resolution training for high-resolution image synthesis
Generative models operate at fixed resolution, even though natural images come in a variety
of sizes. As high-resolution details are downsampled away and low-resolution images are …
of sizes. As high-resolution details are downsampled away and low-resolution images are …
Global learnable attention for single image super-resolution
Self-similarity is valuable to the exploration of non-local textures in single image super-
resolution (SISR). Researchers usually assume that the importance of non-local textures is …
resolution (SISR). Researchers usually assume that the importance of non-local textures is …
Coser: Bridging image and language for cognitive super-resolution
Existing super-resolution (SR) models primarily focus on restoring local texture details often
neglecting the global semantic information within the scene. This oversight can lead to the …
neglecting the global semantic information within the scene. This oversight can lead to the …