[HTML][HTML] A Multi-Branch Feature Extraction Residual Network for Lightweight Image Super-Resolution
C Liu, X Wan, G Gao - Mathematics, 2024 - mdpi.com
Single-image super-resolution (SISR) seeks to elucidate the mapping relationships between
low-resolution and high-resolution images. However, high-performance network models …
low-resolution and high-resolution images. However, high-performance network models …
Recurrent multi-scale approximation-guided network for single image super-resolution
WY Hsu, PW Jian - ACM Transactions on Multimedia Computing …, 2023 - dl.acm.org
Single-image super-resolution (SISR) is an essential topic in computer vision applications.
However, most CNN-based SISR approaches directly learn the relationship between low …
However, most CNN-based SISR approaches directly learn the relationship between low …
Multi-FusNet of Cross Channel Network for Image Super-Resolution
W Ruangsang, S Aramvith, T Onoye - IEEE Access, 2023 - ieeexplore.ieee.org
Image Super-resolution (SR) has gained considerable attention in artificial intelligence (AI)
research and image-based applications. Recent deep learning-based SR models have …
research and image-based applications. Recent deep learning-based SR models have …
Efficient Dual-branch Information Interaction Network for Lightweight Image Super-Resolution
Recently, deep convolutional neural networks (CNNs) have achieved remarkable success in
single-image super-resolution (SISR) tasks. However, these methods often suffer from high …
single-image super-resolution (SISR) tasks. However, these methods often suffer from high …
TAKDSR: Teacher Assistant Knowledge Distillation Framework for Graphics Image Super-Resolution
This paper presents a framework for effectively applying knowledge distillation (KD) to super-
resolution (SR) tasks for computer graphics (CG) images. Specifically, we propose TAKDSR …
resolution (SR) tasks for computer graphics (CG) images. Specifically, we propose TAKDSR …