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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
07 Jun 2010
TL;DR: A novel reliability based view synthesis method using two references and their depth maps that outperforms state-of-the-art view interpolation methods both at eliminating artifacts and improving PSNR.
Abstract: View synthesis using depth maps is a crucial application for Free-viewpoint TV (FTV). In this paper, we propose a novel reliability based view synthesis method using two references and their depth maps. The depth estimation with stereo matching is known to be error-prone, leading to noticeable artifacts in the synthesized new views. In order to provide plausible virtual views for FTV, our focus is on the error suppression for the synthesized view. We innovatively introduce the continuous reliability using error approximation by the reference cross-check. The new view interpolation algorithm is generated with the criterion of Least Sum of Squared Errors (LSSE). Furthermore, the proposed algorithm can be considered as a reliable version of the conventional linear view blending. We experimentally demonstrate the effectiveness of our framework with MPEG standard test sequences. The results show that our method outperforms state-of-the-art view interpolation methods both at eliminating artifacts and improving PSNR.

16 citations

Posted Content
TL;DR: Zhang et al. as discussed by the authors proposed a framework integrated with more reliable supervision guided by semantic co-segmentation and data-augmentation, which excavates mutual semantic from multi-view images to guide the semantic consistency.
Abstract: Recent studies have witnessed that self-supervised methods based on view synthesis obtain clear progress on multi-view stereo (MVS). However, existing methods rely on the assumption that the corresponding points among different views share the same color, which may not always be true in practice. This may lead to unreliable self-supervised signal and harm the final reconstruction performance. To address the issue, we propose a framework integrated with more reliable supervision guided by semantic co-segmentation and data-augmentation. Specially, we excavate mutual semantic from multi-view images to guide the semantic consistency. And we devise effective data-augmentation mechanism which ensures the transformation robustness by treating the prediction of regular samples as pseudo ground truth to regularize the prediction of augmented samples. Experimental results on DTU dataset show that our proposed methods achieve the state-of-the-art performance among unsupervised methods, and even compete on par with supervised methods. Furthermore, extensive experiments on Tanks&Temples dataset demonstrate the effective generalization ability of the proposed method.

16 citations

Journal ArticleDOI
TL;DR: This letter proposes solutions to remove artifacts and apply different filling strategies depending on the nature of each hole, and shows that its method outperforms several view synthesis methods in the quantitative evaluation, besides presenting consistent visual results for both large baselines and severely occluded scenes.
Abstract: Depth-image-based rendering is a popular way to produce content for three-dimensional television and free viewpoint video, allowing the synthesis of numerous viewpoints using a single reference view and its depth map Due to the synthesis process and nature of the input, artifacts and holes appear, and solving these problems becomes a challenge In this letter, we propose solutions to remove those artifacts and apply different filling strategies depending on the nature of each hole Cracks are identified and filled using very local neighborhood information Regions classified as ghosts are projected to their correct place The remaining holes are classified as disocclusions or out-of-field areas, and filled with an appropriate adaptation of a popular inpainting method In both adaptations, patch matching explores the spatial locality concept, using dynamically adaptive patch sizes from the reference image For disocclusions we propose a filling order using depth and background terms, and a searching process that considers only background patches We show that our method outperforms several view synthesis methods in the quantitative evaluation, besides presenting consistent visual results for both large baselines and severely occluded scenes

16 citations

Patent
28 Sep 2012
TL;DR: In this paper, a depth block is generated based on a corresponding reference depth image and the motion or disparity vector is obtained from neighboring blocks, then, predictive coding for the current block using the prediction block.
Abstract: Videos of a scene are processed for view synthesis. The videos are acquired by corresponding cameras arranged so that a view of each camera overlaps with the view of at least one other camera. For each current block, motion or disparity vector is obtained from neighboring blocks. A depth block is based on a corresponding reference depth image and the motion or disparity vector. A prediction block is generated based on the depth block using backward warping. Then, predictive coding for the current block using the prediction block.

16 citations

Proceedings ArticleDOI
28 May 2000
TL;DR: A multi-view image compression system that is capable of providing sufficient and reliable disparity information for intermediate view synthesis is proposed in this paper for 3-D virtual reality applications.
Abstract: A multi-view image compression system that is capable of providing sufficient and reliable disparity information for intermediate view synthesis is proposed in this paper for 3-D virtual reality applications. In the first part of this paper, we develop a codec that features random access to any encoded view. The codec performance is good and comparable to the MPEG standard. In the second part, we interpolate the disparities and refer to appropriate decoded images for the synthesis of any intermediate views. Our design provides enough information so that each synthesis can be achieved within 0.04 sec for a 320/spl times/240 image (excluding the decoding time). An eye glass viewer with infrared synchronization is also adopted to view the stereo results which are very good.

16 citations


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