15 citations · 18 across the 4 of their papers we have counts for
4 papers
Cuboid-Net: A Multi-Branch Convolutional Neural Network for Joint Space-Time Video Super Resolution
Congrui Fu, Hui Yuan, Hongji Xu +2
The demand for high-resolution videos has been consistently rising across various domains, propelled by continuous advancements in science, technology, and societal. Nonetheless, c…
3DAttGAN: A 3D Attention-based Generative Adversarial Network for Joint Space-Time Video Super-Resolution
Congrui Fu, Hui Yuan, Liquan Shen +2
In many applications, including surveillance, entertainment, and restoration, there is a need to increase both the spatial resolution and the frame rate of a video sequence. The ai…
OMR-NET: a two-stage octave multi-scale residual network for screen content image compression
Shiqi Jiang, Ting Ren, Congrui Fu +2
Screen content (SC) differs from natural scene (NS) with unique characteristics such as noise-free, repetitive patterns, and high contrast. Aiming at addressing the inadequacies of…
Global Spatial-Temporal Information-based Residual ConvLSTM for Video Space-Time Super-Resolution
Congrui Fu, Hui Yuan, Shiqi Jiang +3
By converting low-frame-rate, low-resolution videos into high-frame-rate, high-resolution ones, space-time video super-resolution techniques can enhance visual experiences and faci…