Reference-based Super-Resolution

14 papers with code • 1 benchmarks • 0 datasets

Reference-based Super-Resolution aims to recover high-resolution images by utilizing external reference images containing similar content to generate rich textures.

Most implemented papers

Image Super-Resolution by Neural Texture Transfer


Reference-based super-resolution (RefSR), on the other hand, has proven to be promising in recovering high-resolution (HR) details when a reference (Ref) image with similar content as that of the LR input is given.

Dual-Camera Super-Resolution with Aligned Attention Modules

Tengfei-Wang/DualCameraSR ICCV 2021

We present a novel approach to reference-based super-resolution (RefSR) with the focus on dual-camera super-resolution (DCSR), which utilizes reference images for high-quality and high-fidelity results.

Self-Supervised Learning for Real-World Super-Resolution from Dual Zoomed Observations

cszhilu1998/selfdzsr 2 Mar 2022

For this purpose, we take the telephoto image instead of an additional high-resolution image as the supervision information and select a center patch from it as the reference to super-resolve the corresponding short-focus image patch.

Self-Supervised Learning for Real-World Super-Resolution from Dual and Multiple Zoomed Observations

cszhilu1998/selfdzsr 3 May 2024

In addition, we further take multiple zoomed observations to explore self-supervised RefSR, and present a progressive fusion scheme for the effective utilization of reference images.

CrossNet: An End-to-end Reference-based Super Resolution Network using Cross-scale Warping

htzheng/ECCV2018_CrossNet_RefSR ECCV 2018

The Reference-based Super-resolution (RefSR) super-resolves a low-resolution (LR) image given an external high-resolution (HR) reference image, where the reference image and LR image share similar viewpoint but with significant resolution gap x8.

Robust Reference-Based Super-Resolution With Similarity-Aware Deformable Convolution

Slime0519/CVPR_2020_SSEN CVPR 2020

In this paper, we propose a novel and efficient reference feature extraction module referred to as the Similarity Search and Extraction Network (SSEN) for reference-based super-resolution (RefSR) tasks.

Robust Reference-based Super-Resolution via C2-Matching

yumingj/C2-Matching CVPR 2021

However, performing local transfer is difficult because of two gaps between input and reference images: the transformation gap (e. g. scale and rotation) and the resolution gap (e. g. HR and LR).

Coarse-to-Fine Embedded PatchMatch and Multi-Scale Dynamic Aggregation for Reference-based Super-Resolution

zj-binxia/amsa 12 Jan 2022

To improve matching efficiency, we design a novel Embedded PatchMacth scheme with random samples propagation, which involves end-to-end training with asymptotic linear computational cost to the input size.

HSTR-Net: High Spatio-Temporal Resolution Video Generation For Wide Area Surveillance

umutsuluhan/HSTRNet-Interp 9 Apr 2022

Wide area surveillance has many applications and tracking of objects under observation is an important task, which often needs high spatio-temporal resolution (HSTR) video for better precision.

Reference-based Image Super-Resolution with Deformable Attention Transformer

caojiezhang/datsr 25 Jul 2022

Reference-based image super-resolution (RefSR) aims to exploit auxiliary reference (Ref) images to super-resolve low-resolution (LR) images.