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This AI recreated a whole virtual San Francisco from 2.8 million photos

AI-generated imagery and 3D content have come a long way in a very short space of time. It was only two years ago that Google researchers revealed NeRF, or Neural Radiance Fields, and less than two weeks ago NVIDIA blew us away with almost real-time generation of 3D scenes from just a few dozen still photographs using their “Instant NeRF” techniques.

Well, now, a new paper has been released by the folks at Waymo describing “Block-NeRF“, a technique for “scalable large scene neural view synthesis” – basically, generating really really large environments. And as a proof of concept, they recreated the city of San Francisco from 2.8 million photographs. And this video, Károly Zsolnai-Fehér at Two Minute Papers explains how it all works.

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This crazy new NVIDIA tech turns 2D photos into fully 3D scenes in seconds

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Creating 3-dimensional worlds and objects from flat 2-dimensional photographs isn’t a new concept. It’s been happening for years. In the early days (and still often, today), we used photographs inside 3D modelling software as reference images for our 3D creations. A few years pass and along comes photogrammetry, allowing the automatic creation of 3D models and scenes from a couple of hundred photos.

Photogrammetry often takes hours, but this new tech from NVIDIA can do it in seconds. And you don’t need hundreds of images in order to do it, either. Just a few dozen. The tech demo above illustrates the principle where NVIDIA reproduces an iconic image of Andy Warhol shooting a Polaroid camera and with just a relatively handful of images, it gets turned into a 3D scene with a virtual camera that can fly around it with ease.

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You can now 3D scan objects with any iPhone – even if it doesn’t have a LIDAR sensor

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As more people have gotten into 3D printing, not to mention combining 3D objects with photographs, 3D scanning has become a big thing. Especially, apparently, when it comes to smartphones. With many smartphones featuring Time of Flight depth sensors these days, though, that’s not much of a surprise. Not all phones feature one, though, which has made things a little tricky.

Now, though, it looks like the folks at Polycam have figured out a solution that just uses the regular normal flat 2D camera of the iPhone to create 3D objects that you can bring right into your CG scenes. Unfortunately, yes, you read that right. iPhone. No word on Android yet – although there are rumours.

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This AI uses tourist photos to create mind-blowing 3D renderings

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A team of researchers at Google has come up with really awesome use of all those photos of popular tourist spots. They’ve created an algorithm that takes those photos and turns them into realistic and very detailed 3D renderings. And the best of all is that it even edits out interfering objects and evens out the changes in lighting.

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Experimenting with photogrammetry at home

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This is going to be a long one…

Photogrammetry is my hobby for the last couple of years. My first try was a small wooden Piggy from four or five years ago. That was done with a mobile phone (Nexus 4) without any knowledge of proper lighting, manual control of the camera, balancing photos, etc. The scanned result was pretty bad, but I learned a lot from it. After that, I bought a Canon EOS700D with kit lens and started to learn more about the proper way to take photos, how to correct them and how to work on the scanned geometry. Results got a lot better with the proper equipment

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Automating image capture for 3D scanning through photogrammetry


3D data creation is part of a growing trend in the use of computational imaging techniques within cultural heritage digitization shops. In particular, operational adoption of photogrammetry has been witnessed at such institutions as the Minneapolis Institute of Art (MIA), the Smithsonian, and the University of Virginia Library.

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