Exploiting multi-scale parallel self-attention and local variation via dual-branch transformer-CNN structure for face super-resolution
Recently, deep learning technique has been widely employed to deal with face super-
resolution (FSR) problem. It aims to predict the nonlinear relationship between the low …
resolution (FSR) problem. It aims to predict the nonlinear relationship between the low …
Learning motion-robust remote photoplethysmography through arbitrary resolution videos
Remote photoplethysmography (rPPG) enables non-contact heart rate (HR) estimation from
facial videos which gives significant convenience compared with traditional contact-based …
facial videos which gives significant convenience compared with traditional contact-based …
[PDF][PDF] Learning Attention from Attention: Efficient Self-Refinement Transformer for Face Super-Resolution.
Recently, Transformer-based architecture has been introduced into face super-resolution
task due to its advantage in capturing long-range dependencies. However, these …
task due to its advantage in capturing long-range dependencies. However, these …
Video Super-Resolution Using Plug-and-Play Priors
MC Zerva, LP Kondi - IEEE Access, 2024 - ieeexplore.ieee.org
Video super-resolution is a fundamental task in computer vision, aiming to enhance the
resolution and visual quality of low-resolution videos. Plug-and-Play Priors is one of the …
resolution and visual quality of low-resolution videos. Plug-and-Play Priors is one of the …
CTE-Net: Contextual Texture Enhancement Network for Image Super-Resolution
The object of image super-resolution reconstruction is to overcome the limitations imposed
by hardware imaging conditions and patterns, aiming to restore high-frequency details in …
by hardware imaging conditions and patterns, aiming to restore high-frequency details in …
PLGNet: Prior-guided Local and Global Interactive Hybrid Network for Face Super-Resolution
Recent CNN-driven face super-resolution (FSR) technologies have achieved excellent
breakthroughs by incorporating facial prior knowledge. However, most of them suffer from …
breakthroughs by incorporating facial prior knowledge. However, most of them suffer from …
HyFormer: Hybrid Grouping-Aggregation Transformer and Wide-Spanning CNN for Hyperspectral Image Super-Resolution
Hyperspectral image (HSI) super-resolution is a practical and challenging task as it requires
the reconstruction of a large number of spectral bands. Achieving excellent reconstruction …
the reconstruction of a large number of spectral bands. Achieving excellent reconstruction …
Synergizing frequency domain and texture-aware implicit module for MRI arbitrary-scale super-resolution
X Tu, G Li, Y Liu - Biomedical Signal Processing and Control, 2024 - Elsevier
Arbitrary-scale MR image super-resolution (SR) methods have emerged as a prominent
research topic in medical imaging due to their ability to address the demand for continuous …
research topic in medical imaging due to their ability to address the demand for continuous …
A Novel Multiclass Object Detection Dataset Enriched With Frequency Data
C Sharma, S Ghosh, KBA Shenoy… - IEEE Access, 2024 - ieeexplore.ieee.org
Video analysis has attracted the attention of many researchers because of the growing need
for multimedia information retrieval for computer vision applications. Content based retrieval …
for multimedia information retrieval for computer vision applications. Content based retrieval …
Attention-Guided Multi-scale Interaction Network for Face Super-Resolution
Recently, CNN and Transformer hybrid networks demonstrated excellent performance in
face super-resolution (FSR) tasks. Since numerous features at different scales in hybrid …
face super-resolution (FSR) tasks. Since numerous features at different scales in hybrid …