30 citations · 89 across the 25 of their papers we have counts for
6 papers · 1 filter
Bi-Noising Diffusion: Towards Conditional Diffusion Models with Generative Restoration Priors
Kangfu Mei, Nithin Gopalakrishnan Nair, Vishal M. Patel
Conditional diffusion probabilistic models can model the distribution of natural images and can generate diverse and realistic samples based on given conditions. However, oftentime…
VIDM: Video Implicit Diffusion Models
Kangfu Mei, Vishal M. Patel
Diffusion models have emerged as a powerful generative method for synthesizing high-quality and diverse set of images. In this paper, we propose a video generation method based on…
AT-DDPM: Restoring Faces degraded by Atmospheric Turbulence using Denoising Diffusion Probabilistic Models
Nithin Gopalakrishnan Nair, Kangfu Mei, Vishal M. Patel
Although many long-range imaging systems are designed to support extended vision applications, a natural obstacle to their operation is degradation due to atmospheric turbulence. A…
Deep Semantic Statistics Matching (D2SM) Denoising Network
Kangfu Mei, Vishal M. Patel, Rui Huang
The ultimate aim of image restoration like denoising is to find an exact correlation between the noisy and clear image domains. But the optimization of end-to-end denoising learnin…
A comparison of different atmospheric turbulence simulation methods for image restoration
Nithin Gopalakrishnan Nair, Kangfu Mei, Vishal M. Patel
Atmospheric turbulence deteriorates the quality of images captured by long-range imaging systems by introducing blur and geometric distortions to the captured scene. This leads to…
Thermal to Visible Image Synthesis under Atmospheric Turbulence
Kangfu Mei, Yiqun Mei, Vishal M. Patel
In many practical applications of long-range imaging such as biometrics and surveillance, thermal imagining modalities are often used to capture images in low-light and nighttime c…