Hole-filling approach based on convolutional neural network for depth image-based rendering view synthesis

2020 ◽  
Vol 29 (01) ◽  
pp. 1
Author(s):  
Chengtao Cai ◽  
Bing Fan ◽  
Haiyang Meng ◽  
Qidan Zhu
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
View Synthesis ◽  
Depth Image ◽  
Hole Filling ◽  
Image Based Rendering ◽  
Depth Image Based Rendering

A BACKGROUND MODELING-BASED FAITHFUL APPROACH TO THE DISOCCLUSION PROBLEM IN DEPTH IMAGE-BASED RENDERING

2013 ◽  
Vol 27 (02) ◽  
pp. 1354005 ◽  
Author(s):  
MICHAEL SCHMEING ◽  
XIAOYI JIANG
Keyword(s):  
Background Modeling ◽  
View Synthesis ◽  
Depth Image ◽  
Image Based Rendering ◽  
Texture Information ◽  
Depth Image Based Rendering ◽  
Compression Artifacts

In this paper, we address the disocclusion problem that occurs during view synthesis in depth image-based rendering (DIBR). We propose a method that can recover faithful texture information for disoccluded areas. In contrast to common disocclusion filling methods, which usually work frame-by-frame, our algorithm can take information from temporally neighboring frames into account. This way, we are able to reconstruct a faithful filling for the disocclusion regions and not just an approximate or plausible one. Our method avoids artifacts that occur with common approaches and can additionally reduce compression artifacts at object boundaries.

Hole-filling Based on Disparity Map and Inpainting for Depth-Image-Based Rendering

2016 ◽  
Vol 9 (5) ◽  
pp. 145-164 ◽  
Author(s):  
Ran Liu ◽  
Zekun Deng ◽  
Lin Yi ◽  
Zhenwei Huang ◽  
Donghua Cao ◽  
...  
Keyword(s):  
Depth Image ◽  
Disparity Map ◽  
Hole Filling ◽  
Image Based Rendering ◽  
Depth Image Based Rendering

Hole Filling Method for Depth Image Based Rendering Based on Boundary Decision

2017 ◽  
Vol 24 (3) ◽  
pp. 329-333 ◽  
Author(s):  
Jea-Hyung Cho ◽  
Wonseok Song ◽  
Hyuk Choi ◽  
Taejeong Kim
Keyword(s):  
Depth Image ◽  
Hole Filling ◽  
Image Based Rendering ◽  
Depth Image Based Rendering ◽  
Filling Method
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