Super-Resolution Stereo- and Multi-View Synthesis from Monocular Video Sequences

2007 ◽  
Author(s):  
Sebastian Knorr ◽  
Matthias Kunter ◽  
Thomas Sikora
Keyword(s):  
Super Resolution ◽  
View Synthesis ◽  
Video Sequences ◽  
Monocular Video

Super-Resolution Face View Synthesis using a Mobile Face Capture System

2006 ◽  
Author(s):  
Miguel A. Figueroa-villanueva ◽  
George C. Stockman
Keyword(s):  
Super Resolution ◽  
View Synthesis ◽  
Face View

A Fast View Synthesis Implementation Method for Light Field Applications

2021 ◽  
Vol 17 (4) ◽  
pp. 1-20
Author(s):  
Wei Gao ◽  
Linjie Zhou ◽  
Lvfang Tao
Keyword(s):  
Neural Networks ◽  
Light Field ◽  
Three Dimensional ◽  
Super Resolution ◽  
View Synthesis ◽  
Compact Representation ◽  
Light Weight ◽  
Computationally Efficient ◽  
Full Resolution ◽  
Time Systems

View synthesis (VS) for light field images is a very time-consuming task due to the great quantity of involved pixels and intensive computations, which may prevent it from the practical three-dimensional real-time systems. In this article, we propose an acceleration approach for deep learning-based light field view synthesis, which can significantly reduce calculations by using compact-resolution (CR) representation and super-resolution (SR) techniques, as well as light-weight neural networks. The proposed architecture has three cascaded neural networks, including a CR network to generate the compact representation for original input views, a VS network to synthesize new views from down-scaled compact views, and a SR network to reconstruct high-quality views with full resolution. All these networks are jointly trained with the integrated losses of CR, VS, and SR networks. Moreover, due to the redundancy of deep neural networks, we use the efficient light-weight strategy to prune filters for simplification and inference acceleration. Experimental results demonstrate that the proposed method can greatly reduce the processing time and become much more computationally efficient with competitive image quality.

Edge Orientation Driven Depth Super-Resolution for View Synthesis

2019 ◽  
pp. 107-121
Author(s):  
Chao Yao ◽  
Jimin Xiao ◽  
Jian Jin ◽  
Xiaojuan Ban
Keyword(s):  
Super Resolution ◽  
View Synthesis ◽  
Edge Orientation

Unsupervised virtual view synthesis from monocular video with generative adversarial warping

2021 ◽  
Vol 96 ◽  
pp. 107460
Author(s):  
Xiaochuan Wang ◽  
Yi Liu ◽  
Haisheng Li
Keyword(s):  
View Synthesis ◽  
Virtual View Synthesis ◽  
Virtual View ◽  
Monocular Video

Understanding Video Sequences through Super-Resolution

2011 ◽  
pp. 25-34
Author(s):  
Yu Peng ◽  
Jesse S. Jin ◽  
Suhuai Luo ◽  
Mira Park
Keyword(s):  
Super Resolution ◽  
Video Sequences

Blind Super Resolution of Real-Life Video Sequences

2016 ◽  
Vol 25 (4) ◽  
pp. 1544-1555 ◽  
Author(s):  
Esmaeil Faramarzi ◽  
Dinesh Rajan ◽  
Felix C. A. Fernandes ◽  
Marc P. Christensen
Keyword(s):  
Real Life ◽  
Super Resolution ◽  
Video Sequences

Variable structure multiple model for articulated human motion tracking from monocular video sequences

2012 ◽  
Vol 55 (5) ◽  
pp. 1138-1150 ◽  
Author(s):  
Hong Han ◽  
MingLei Tong ◽  
ZhiChao Chen ◽  
YouJian Fan
Keyword(s):  
Motion Tracking ◽  
Variable Structure ◽  
Human Motion ◽  
Video Sequences ◽  
Multiple Model ◽  
Human Motion Tracking ◽  
Monocular Video ◽  
Articulated Human Motion

scholarly journals Spatial, Temporal, and Interchannel Image Data Fusion for Long-Distance Terrestrial Observation Systems

2008 ◽  
Vol 2008 ◽  
pp. 1-18 ◽  
Author(s):  
Barak Fishbain ◽  
Leonid P. Yaroslavsky ◽  
Ianir Ideses
Keyword(s):  
Data Fusion ◽  
Visual Analysis ◽  
Real Life ◽  
Super Resolution ◽  
Image Data ◽  
Video Sequences ◽  
Long Distance ◽  
Image Stabilization ◽  
Thermal Range ◽  
Observation Systems

This paper presents methods for intrachannel and interchannel fusion of thermal and visual sensors used in long-distance terrestrial observation systems. Intrachannel spatial and temporal fusion mechanisms used for image stabilization, super-resolution, denoising, and deblurring are supplemented by interchannel data fusion of visual- and thermal-range channels for generating fused videos intended for visual analysis by a human operator. Tests on synthetic, as well as on real-life, video sequences have confirmed the potential of the suggested methods.

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