View synthesis
In today's world, View synthesis has become a topic of great importance and interest to a wide variety of individuals and organizations. From its impact on society to its implications on the economy, View synthesis has captured the attention of experts and everyday people alike. In this article, we will explore the different aspects related to View synthesis, from its evolution over time to its influence on the world today. Through in-depth analysis, we will seek to better understand the importance of View synthesis and how it is shaping our present and future.
In computer graphics, view synthesis, or novel view synthesis, is a task which consists of generating images of a specific subject or scene from a specific point of view, when the only available information is pictures taken from different points of view.[1]
This task was only recently (late 2010s – early 2020s) tackled with significant success, mostly as a result of advances in machine learning. Notable successful methods are Neural Radiance Fields and 3D Gaussian Splatting.
Applications of view synthesis are numerous, one of them being Free viewpoint television.
See also
References
- ^ "Velasco, Jose Maria", Benezit Dictionary of Artists, Oxford University Press, 2011-10-31, doi:10.1093/benz/9780199773787.article.b00189225, retrieved 2024-03-31
External links
- Shuai Li; Ce Zhu; Ming-Ting Sun (2018). "Hole Filling with Multiple Reference Views in DIBR View Synthesis". IEEE Transactions on Multimedia. 20 (8): 1948–1959. arXiv:1802.03079. Bibcode:2018arXiv180203079L. doi:10.1109/TMM.2018.2791810. S2CID 33449031.
- Ce Zhu; Shuai Li (2016). "Depth Image Based View Synthesis: New Insights and Perspectives on Hole Generation and Filling". IEEE Transactions on Broadcasting. 62 (1): 82–93. doi:10.1109/TBC.2015.2475697. S2CID 19100077.
- Mansi Sharma; Santanu Chaudhury; Brejesh Lall (2014). Kinect-Variety Fusion: A Novel Hybrid Approach for Artifacts-Free 3DTV Content Generation. In 22nd International Conference on Pattern Recognition (ICPR), Stockholm, 2014. doi:10.1109/ICPR.2014.395.
- Webcam lets users eyeball others BBC
- https://web.archive.org/web/20060905013927/http://www.cs.wisc.edu/computer-vision/projects/interp/interp.html
- http://homepages.inf.ed.ac.uk/rbf/CVonline/LOCAL_COPIES/FUSIELLO4/tutorial.html#x1-10001
- https://web.archive.org/web/20061126225514/http://www-sop.inria.fr/robotvis/personnel/fabad/PhD/index.html
- http://www.cs.huji.ac.il/labs/vision/demos/synthesis/synthesis.html
- http://www.hpl.hp.com/research/mmsl/projects/graphics/chromaglyph/index.html
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