Results 201 to 210 of about 3,131,923 (261)

Visual Noise Mask for Human Point-Light Displays: A Coding-Free Approach. [PDF]

NeuroSci
Senra CC, Sampaio ACS, Lapenta OM.
europepmc   +1 more source

Investigation of the stochastic behaviour of two-phase system with a coupled analysis of electrochemical noise and video images.

, 2005
H. Bouazaze
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ELIMINATION OF WHITE NOISE FROM VIDEO SIGNALS OF TELEVISION TRANSMISSION BY USING DIGITAL RECURSIVE ESTIMATION

, 2012
Mehmet Engin, Rasim Saltuk Alakus, Erkan Zeki Engın   +2 more
openalex   +1 more source

Green noise video halftoning

2014 19th International Conference on Digital Signal Processing, 2014
Video halftoning is a technology used to render a video onto a display device that can only display limited number of levels. Conventional video halftoning algorithms produce blue noise video halftones which are prone to flickering. Dedicated deflickering processes are hence required to reduce flickering.
Yuk-Hee Chan, Yik Hing Fung
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Preserve Your Own Correlation: A Noise Prior for Video Diffusion Models

IEEE International Conference on Computer Vision, 2023
Despite tremendous progress in generating high-quality images using diffusion models, synthesizing a sequence of animated frames that are both photorealistic and temporally coherent is still in its infancy.
Songwei Ge, Seungjun Nah, Guilin Liu, Tyler Poon, Andrew Tao, Bryan Catanzaro, David Jacobs, Jia-Bin Huang, Ming-Yu Liu, Y. Balaji   +9 more
semanticscholar   +1 more source

FreeNoise: Tuning-Free Longer Video Diffusion via Noise Rescheduling

International Conference on Learning Representations, 2023
With the availability of large-scale video datasets and the advances of diffusion models, text-driven video generation has achieved substantial progress.
Haonan Qiu, Menghan Xia, Yong Zhang, Yin-Yin He, Xintao Wang, Ying Shan, Ziwei Liu   +6 more
semanticscholar   +1 more source

Deep Unfolding Network for Efficient Mixed Video Noise Removal

IEEE transactions on circuits and systems for video technology (Print), 2023
Existing image and video denoising algorithms have focused on removing homogeneous Gaussian noise. However, this assumption with noise modeling is often too simplistic for the characteristics of real-world noise.
Lu Sun, Yichen Wang, Fangfang Wu, Xin Li, W. Dong, Guangming Shi   +5 more
semanticscholar   +1 more source

VideoFusion: Decomposed Diffusion Models for High-Quality Video Generation

Computer Vision and Pattern Recognition, 2023
A diffusion probabilistic model (DPM), which constructs a forward diffusion process by gradually adding noise to data points and learns the reverse denoising process to generate new samples, has been shown to handle complex data distribution. Despite its
Zhengxiong Luo, Dayou Chen, Yingya Zhang, Yan Huang, Liangsheng Wang, Yujun Shen, Deli Zhao, Jinren Zhou, Tien-Ping Tan   +8 more
semanticscholar   +1 more source