54 citations · 63 across the 4 of their papers we have counts for
4 papers
Task-Aware Dynamic Transformer for Efficient Arbitrary-Scale Image Super-Resolution
Tianyi Xu, Yiji Zhou, Xiaotao Hu +4
Arbitrary-scale super-resolution (ASSR) aims to learn a single model for image super-resolution at arbitrary magnifying scales. Existing ASSR networks typically comprise an off-the…
Scale-Adaptive Feature Aggregation for Efficient Space-Time Video Super-Resolution
Zhewei Huang, Ailin Huang, Xiaotao Hu +3
The Space-Time Video Super-Resolution (STVSR) task aims to enhance the visual quality of videos, by simultaneously performing video frame interpolation (VFI) and video super-resolu…
A Dynamic Multi-Scale Voxel Flow Network for Video Prediction
Xiaotao Hu, Zhewei Huang, Ailin Huang +2
The performance of video prediction has been greatly boosted by advanced deep neural networks. However, most of the current methods suffer from large model sizes and require extra…
Semi-Cycled Generative Adversarial Networks for Real-World Face Super-Resolution
Hao Hou, Jun Xu, Yingkun Hou +3
Real-world face super-resolution (SR) is a highly ill-posed image restoration task. The fully-cycled Cycle-GAN architecture is widely employed to achieve promising performance on f…