4 citations · 5 across the 12 of their papers we have counts for
12 papers
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,…
iHDR: Iterative HDR Imaging with Arbitrary Number of Exposures
Yu Yuan, Yiheng Chi, Xingguang Zhang +1
High dynamic range (HDR) imaging aims to obtain a high-quality HDR image by fusing information from multiple low dynamic range (LDR) images. Numerous learning-based HDR imaging met…
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…
Source-free Domain Adaptation for Video Object Detection Under Adverse Image Conditions
Xingguang Zhang, Chih-Hsien Chou
When deploying pre-trained video object detectors in real-world scenarios, the domain gap between training and testing data caused by adverse image conditions often leads to perfor…
Spatio-Temporal Turbulence Mitigation: A Translational Perspective
Xingguang Zhang, Nicholas Chimitt, Yiheng Chi +2
Recovering images distorted by atmospheric turbulence is a challenging inverse problem due to the stochastic nature of turbulence. Although numerous turbulence mitigation (TM) algo…
Physics-Driven Turbulence Image Restoration with Stochastic Refinement
Ajay Jaiswal, Xingguang Zhang, Stanley H. Chan +1
Image distortion by atmospheric turbulence is a stochastic degradation, which is a critical problem in long-range optical imaging systems. A number of research has been conducted d…
FarSight: A Physics-Driven Whole-Body Biometric System at Large Distance and Altitude
Feng Liu, Ryan Ashbaugh, Nicholas Chimitt +17
Whole-body biometric recognition is an important area of research due to its vast applications in law enforcement, border security, and surveillance. This paper presents the end-to…
HDR Imaging with Spatially Varying Signal-to-Noise Ratios
Yiheng Chi, Xingguang Zhang, Stanley H. Chan
While today's high dynamic range (HDR) image fusion algorithms are capable of blending multiple exposures, the acquisition is often controlled so that the dynamic range within one…
Scattering and Gathering for Spatially Varying Blurs
Nicholas Chimitt, Xingguang Zhang, Yiheng Chi +1
A spatially varying blur kernel is specified by an input coordinate and an output coordinate .…
Imaging through the Atmosphere using Turbulence Mitigation Transformer
Xingguang Zhang, Zhiyuan Mao, Nicholas Chimitt +1
Restoring images distorted by atmospheric turbulence is a ubiquitous problem in long-range imaging applications. While existing deep-learning-based methods have demonstrated promis…