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View synthesis

About: View synthesis is a research topic. Over the lifetime, 1701 publications have been published within this topic receiving 42333 citations.


Papers
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Proceedings ArticleDOI
11 Nov 2013
TL;DR: A novel view synthesis technique to create a virtual view from two video sequences with corresponding depths is proposed, employing low complexity integer pixel precision warping and a novel approach for hole filling based on inverse mapping.
Abstract: Three-dimensional video has gained much attention during the last decade due its vast applications in cinema, television, animation and virtual reality. The design of intermediate view synthesis algorithms that are efficient both in terms of computational complexity and visual quality is a paramount goal in the fields of 3D free view point television and displays. This papers focuses on the design of a low complexity view synthesis algorithm that produces better quality of the virtual image. A novel view synthesis technique to create a virtual view from two video sequences with corresponding depths is proposed. The technique employs low complexity integer pixel precision warping and a novel approach for hole filling based on inverse mapping. The proposed technique is tested over a number of video sequences and compared with existing state of the art methods, yielding excellent results both in terms of signal to noise ratio and visual quality.

28 citations

Posted Content
TL;DR: In this article, a CNN-based approach is proposed to synthesize novel views of the same object or scene observed from arbitrary viewpoints from an input image. But, instead of synthesizing pixels from scratch, they learn to copy them from the input image, which is different from our approach.
Abstract: We address the problem of novel view synthesis: given an input image, synthesizing new images of the same object or scene observed from arbitrary viewpoints. We approach this as a learning task but, critically, instead of learning to synthesize pixels from scratch, we learn to copy them from the input image. Our approach exploits the observation that the visual appearance of different views of the same instance is highly correlated, and such correlation could be explicitly learned by training a convolutional neural network (CNN) to predict appearance flows -- 2-D coordinate vectors specifying which pixels in the input view could be used to reconstruct the target view. Furthermore, the proposed framework easily generalizes to multiple input views by learning how to optimally combine single-view predictions. We show that for both objects and scenes, our approach is able to synthesize novel views of higher perceptual quality than previous CNN-based techniques.

28 citations

Journal ArticleDOI
TL;DR: A convolutional neural network (CNN)-based synthesized view quality enhancement method for 3D high efficiency video coding (HEVC) is proposed, which can efficiently eliminate the artifacts in the synthesized image, and reduce 25.9% and 11.7% bit rate, which significantly outperforms the state-of-the-art methods.
Abstract: The quality of synthesized view plays an important role in the 3D video system. In this paper, to further improve the coding efficiency, a convolutional neural network (CNN)-based synthesized view quality enhancement method for 3D high efficiency video coding (HEVC) is proposed. First, the distortion elimination in synthesized view is formulated as an image restoration task with the aim to reconstruct the latent distortion free synthesized image. Second, the learned CNN models are incorporated into 3D HEVC codec to improve the view synthesis performance for both view synthesis optimization (VSO) and the final synthesized view, where the geometric and compression distortions are considered according to the specific characteristics of synthesized view. Third, a new Lagrange multiplier in the rate-distortion cost function is derived to adapt the CNN-based VSO process to embrace a better 3D video coding performance. Extensive experimental results show that the proposed scheme can efficiently eliminate the artifacts in the synthesized image, and reduce 25.9% and 11.7% bit rate in terms of peak-signal-to-noise ratio and structural similarity index, which significantly outperforms the state-of-the-art methods.

28 citations

Journal ArticleDOI
TL;DR: This work presents a new bio-inspired approach applied to a problem of stereo image matching based on an artificial epidemic process, which it is called the infection algorithm, based on a set of distributed rules.
Abstract: We present a new bio-inspired approach applied to a problem of stereo image matching. This approach is based on an artificial epidemic process, which we call the infection algorithm. The problem at hand is a basic one in computer vision for 3D scene reconstruction. It has many complex aspects and is known as an extremely difficult one. The aim is to match the contents of two images in order to obtain 3D information that allows the generation of simulated projections from a viewpoint that is different from the ones of the initial photographs. This process is known as view synthesis. The algorithm we propose exploits the image contents in order to produce only the necessary 3D depth information, while saving computational time. It is based on a set of distributed rules, which propagate like an artificial epidemic over the images. Experiments on a pair of real images are presented, and realistic reprojected images have been generated.

28 citations

Proceedings ArticleDOI
29 Dec 2011
TL;DR: Results show that the most commonly used objective metrics can be far from human judgment depending on the artifact to deal with.
Abstract: This paper addresses the problem of evaluating virtual view synthesized images in the multi-view video context. As a matter of fact, view synthesis brings new types of distortion. The question refers to the ability of the traditional used objective metrics to assess synthesized views quality, considering the new types of artifacts. The experiments conducted to determine their reliability consist in assessing seven different view synthesis algorithms. Subjective and objective measurements have been performed. Results show that the most commonly used objective metrics can be far from human judgment depending on the artifact to deal with.

27 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202354
2022117
2021189
2020158
2019114
2018102