5 papers
Progressive Image Restoration via Text-Conditioned Video Generation
Peng Kang, Xijun Wang, Yu Yuan
Recent text-to-video models have demonstrated strong temporal generation capabilities, yet their potential for image restoration remains underexplored. In this work, we repurpose C…
Astrophotography turbulence mitigation via generative models
Joonyeoup Kim, Yu Yuan, Xingguang Zhang +2
Photography is the cornerstone of modern astronomical and space research. However, most astronomical images captured by ground-based telescopes suffer from atmospheric turbulence,…
Learning Phase Distortion with Selective State Space Models for Video Turbulence Mitigation
Xingguang Zhang, Nicholas Chimitt, Xijun Wang +2
Atmospheric turbulence is a major source of image degradation in long-range imaging systems. Although numerous deep learning-based turbulence mitigation (TM) methods have been prop…
Personalized Generative Low-light Image Denoising and Enhancement
Xijun Wang, Prateek Chennuri, Dilshan Godaliyadda +5
Modern cameras' performance in low-light conditions remains suboptimal due to fundamental limitations in photon shot noise and sensor read noise. Generative image restoration metho…
Generative Photography: Scene-Consistent Camera Control for Realistic Text-to-Image Synthesis
Yu Yuan, Xijun Wang, Yichen Sheng +3
Image generation today can produce somewhat realistic images from text prompts. However, if one asks the generator to synthesize a specific camera setting such as creating differen…