1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.CV2025
UltraVSR: Achieving Ultra-Realistic Video Super-Resolution with Efficient One-Step Diffusion Space
Yong Liu, Jinshan Pan, Yinchuan Li +4
Diffusion models have shown great potential in generating realistic image detail. However, adapting these models to video super-resolution (VSR) remains challenging due to their in…
cs.CV2024★ 1 cited
Adapting LLaMA Decoder to Vision Transformer
Jiahao Wang, Wenqi Shao, Mengzhao Chen +7
This work examines whether decoder-only Transformers such as LLaMA, which were originally designed for large language models (LLMs), can be adapted to the computer vision field. We…
cs.CV2024
PatchScaler: An Efficient Patch-Independent Diffusion Model for Image Super-Resolution
Yong Liu, Hang Dong, Jinshan Pan +5
While diffusion models significantly improve the perceptual quality of super-resolved images, they usually require a large number of sampling steps, resulting in high computational…