View synthesis
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][2]
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 view point television. The technique has also been applied to real-estate marketing, where novel views of a listing's interior are generated from a limited set of photographs for use in virtual home staging.[3][4]
See also
References
- ↑ "Velasco, Jose Maria", Benezit Dictionary of Artists (Oxford University Press), 2011-10-31, doi:10.1093/benz/9780199773787.article.b00189225
- ↑ "MultiDiff: Consistent Novel View Synthesis from a Single Image". IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 2024. https://openaccess.thecvf.com/content/CVPR2024/html/Muller_MultiDiff_Consistent_Novel_View_Synthesis_from_a_Single_Image_CVPR_2024_paper.html.
- ↑ Dan, T. (2025). "Generation and Synthesis of Video from Static Images for Real Estate Virtual Tours". 24th RoEduNet Conference: Networking in Education and Research. https://ieeexplore.ieee.org/document/11208456.
- ↑ "AI-based MLS virtual staging workflow and multi-view consistency". Edensign. October 20, 2025. https://edensign.io/customer-stories/how-edensign-powers-mls-virtual-staging.
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. doi:10.1109/TMM.2018.2791810. Bibcode: 2018arXiv180203079L.
- 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.
- 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
- View Synthesis by Image Interpolation
- Elements of Geometric Computer Vision
- Contributions to the problem of novel view synthesis from still pictures
- The Spinning Statue
- http://www.hpl.hp.com/research/mmsl/projects/graphics/chromaglyph/index.html
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