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N-Dimensional Gaussians for Fitting of High Dimensional Functions

67 pointsby jasondaviesabout 1 year ago

3 comments

vessenesabout 1 year ago
When I think of turning sequences of images into gaussians, I think of the difficulty of getting generalizable information that can be re-rendered out of the pipeline; textures and lighting, basically. From the description at the top of the paper, where they mention adding dimensions for things like albedo, I got excited.<p>But the demos don&#x27;t do any re-rendering &#x2F; change of lighting &#x2F; etc, so I can&#x27;t tell if this paper is just a &#x27;super high render quality at same training time&#x27; paper, which is of course great to have, or if it has a shot at being extended to get us scenes that can be adjusted as to lighting and texture in-engine.<p>Any experts care to chime in?
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3abitonabout 1 year ago
This problem specifically (3D reconstruction with representation fitting) is really an overfitting nightmare, they just adapted to it not really overcame it. Nonetheless interesting work.
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hackandthinkabout 1 year ago
I expected Gaussian processes.<p>Can someone relate this to Gaussian processes?
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