This paper reviews the NTIRE 2023 challenge on efficient single-image super-resolution
with a focus on the proposed solutions and results. The aim of this challenge is to devise a …

Guided depth map super-resolution (GDSR), which aims to reconstruct a high-resolution
depth map from a low-resolution observation with the help of a paired high-resolution color …

Deep learning based approaches has achieved great performance in single image super-
resolution (SISR). However, recent advances in efficient super-resolution focus on reducing …

While some studies have proven that Swin Transformer (Swin) with window self-attention
(WSA) is suitable for single image super-resolution (SR), the plain WSA ignores the broad …

This work aims to improve the applicability of diffusion models in realistic image restoration.
Specifically, we enhance the diffusion model in several aspects such as network …

Stereo image super-resolution aims at enhancing the quality of super-resolution results by
utilizing the complementary information provided by binocular systems. To obtain …

ConvNets can compete with transformers in high-level tasks by exploiting larger receptive
fields. To unleash the potential of ConvNet in super-resolution we propose a multi-scale …

This paper introduces a novel benchmark for efficient upscaling as part of the NTIRE 2023
Real-Time Image Super-Resolution (RTSR) Challenge, which aimed to upscale images …

The task of single image super resolution (SISR) has taken much attention in the last few
years due to the wide range of real-world applications. However, most of the recently …

This paper reviews the challenge on constrained high dynamic range (HDR) imaging that
was part of the New Trends in Image Restoration and Enhancement (NTIRE) workshop, held …