5 papers
NSARM: Next-Scale Autoregressive Modeling for Robust Real-World Image Super-Resolution
Xiangtao Kong, Rongyuan Wu, Shuaizheng Liu +2
Most recent real-world image super-resolution (Real-ISR) methods employ pre-trained text-to-image (T2I) diffusion models to synthesize the high-quality image either from random Gau…
AlignCVC: Aligning Cross-View Consistency for Single-Image-to-3D Generation
Xinyue Liang, Zhiyuan Ma, Lingchen Sun +2
Single-image-to-3D models typically follow a sequential generation and reconstruction workflow. However, intermediate multi-view images synthesized by pre-trained generation models…
One-Step Diffusion for Detail-Rich and Temporally Consistent Video Super-Resolution
Yujing Sun, Lingchen Sun, Shuaizheng Liu +3
It is a challenging problem to reproduce rich spatial details while maintaining temporal consistency in real-world video super-resolution (Real-VSR), especially when we leverage pr…
InstructRestore: Region-Customized Image Restoration with Human Instructions
Shuaizheng Liu, Jianqi Ma, Lingchen Sun +2
Despite the significant progress in diffusion prior-based image restoration, most existing methods apply uniform processing to the entire image, lacking the capability to perform r…
Perceive, Understand and Restore: Real-World Image Super-Resolution with Autoregressive Multimodal Generative Models
Hongyang Wei, Shuaizheng Liu, Chun Yuan +1
By leveraging the generative priors from pre-trained text-to-image diffusion models, significant progress has been made in real-world image super-resolution (Real-ISR). However, th…