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a blog of links related to computer animation and production technology Sponsored by ReelMatters.com
Year: 2022
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3D Stereoscopic Photography – SPM/DMAG Free automatic depth map from stereo photos generation
http://3dstereophoto.blogspot.com/p/software.html
http://3dstereophoto.blogspot.com/2015/06/depth-map-automatic-generator-7-dmag7.html
Automatic depth map generation, stereo matching, multi-view stereo, Structure from Motion (SfM), photogrammetry, 2d to 3d conversion, etc.
Software to
– create depth maps from stereo pairs (stereo matching),
– generate intermediate synthetic views (lenticular),
– create depth maps from multiple views (multi-view stereo matching),
– create dense 3D reconstruction (point cloud) from multiple views (structure from motion and multi-view stereo),
– perform 2D to 3D image conversion (stereo conversion),
– perform edge-preserving smoothing,
– rectify/align stereo pairs
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Epic Games to Pay Record $520 Million to Settle FTC Charges Over Child Privacy and Player Manipulation
“The Federal Trade Commission has accused the leading video game developer of manipulating young players into unintentional purchases, illegally collecting personal information of kids under the age of 13, and endangering children by connecting them with strangers in its hugely successful ‘Fortnight’ game.”
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Cinesite group secures $235m funding package
https://www.televisual.com/news/cinesite-group-secures-235m-funding-package/
The Cinesite Group has agreed a new long term financial arrangement that ensures our ability to continue supporting our talent and customers across the world, which is a massive vote of confidence for the talent working within all the studios and what has been built within the Cinesite group
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What is Neural Rendering?
https://www.zumolabs.ai/post/what-is-neural-rendering
“The key concept behind neural rendering approaches is that they are differentiable. A differentiable function is one whose derivative exists at each point in the domain. This is important because machine learning is basically the chain rule with extra steps: a differentiable rendering function can be learned with data, one gradient descent step at a time. Learning a rendering function statistically through data is fundamentally different from the classic rendering methods we described above, which calculate and extrapolate from the known laws of physics.”
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