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A comment on NeRF in the Wild: reconstructing 3D scenes from internet photography. Parent comment

Re:NeRF in the Wild: reconstructing 3D scenes from internet ... by duckworthd on Thursday August 06, 2020 @03:34PM (#24074589)
That's a really cool idea! This technology does a fantastic job at reconstructing static scenes. The moving objects -- people, cars, even flora -- are out of scope here. Why? It's really hard to build a 3D model of something you only see from one direction.
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Re:NeRF in the Wild: reconstructing 3D scenes from internet ... by trilinearnz on Thursday August 06, 2020 @10:28PM (#24077413)
Anyone remember this scene from Enemy of The State (1998)? https://youtu.be/3EwZQddc3kY?t=45

Jon Voight: "Can the computer take us around to the other side?"

Jack Black: "It can HYPOTHESIZE"

:)

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Re:NeRF in the Wild: reconstructing 3D scenes from internet ... by sprafa on Saturday August 08, 2020 @12:19PM (#24092784)
I was amazed at the scene at the time, and thought it was unbelievable. But then i read they had NSA advisors and maybe the US govt might have had access to some sort of primitive photogrammetry at the time?
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Re:NeRF in the Wild: reconstructing 3D scenes from internet ... by airstrike on Thursday August 06, 2020 @05:16PM (#24075550)
But if we know what a car ought to look like in 3D, can't we take the one photo we have from one direction and just fill in the blanks with that a priori 3D knowledge?
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Re:NeRF in the Wild: reconstructing 3D scenes from internet ... by withjive on Thursday August 06, 2020 @06:41PM (#24076190)
Similar to how GPT-3 can be applied not only to create Text, but also fill in missing pieces of Images (ie. complete the missing half of a face).

Would the logical next step, use GPT-3 to create a 3D world? :)

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Re:NeRF in the Wild: reconstructing 3D scenes from internet ... by airstrike on Thursday August 06, 2020 @11:45PM (#24077964)
GPT-3D rolls off the tongue nicely
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Re:NeRF in the Wild: reconstructing 3D scenes from internet ... by jhurliman on Thursday August 06, 2020 @11:38PM (#24077895)
Getting there. This is one part of the puzzle: https://arxiv.org/pdf/2007.11965
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