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AI Makes 3D Models From Photos | Two Minute Papers #122

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Two Minute Papers

The paper “Learning a Probabilistic Latent Space of Object Shapes
via 3D Generative-Adversarial Modeling” and its source code is available here:
http://3dgan.csail.mit.edu/
https://arxiv.org/pdf/1610.07584v2.pdf

More about generative adversarial networks (and some explanations):
Image Editing with Generative Adversarial Networks – https://www.youtube.com/watch?v=pqkpIfu36Os
Image Synthesis From Text With Deep Learning – https://www.youtube.com/watch?v=rAbhypxs1qQ

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37 thoughts on “AI Makes 3D Models From Photos | Two Minute Papers #122”

  6. I wonder if by the end of the century there is still anything left that can't be done with machine learning. It's basically everywhere you look already. I can't wait to see what's next 😀

  10. Does anyone here know how you could construct a 3D model of an object using video, if you knew the exact location of the camera in 3D space (but not the location or distance of the object)?

    I need some starting points to begin my searches and some good papers to read.

    Thank you in advance!

  14. wonder if this app can be used as a pseudo-depth sensor for monocular systems like standalone security cameras or small cheap drones. allows it to build enough of an internal model to navigate its surroundings.

    also feels like this can be the first step in a match moving system, like those raw "scans" are meant to be a sketch or template for the app to build off of rather than being the end product. like it's the raw volumetric data the app gleans off the photo that it then compares and contrasts with more refined meshes in its database.
    there is an app that debuted around 2013 called 3-sweep that let you trace 3d models from 2d images by way of an automatic edge detect + symmetrize function and a year after that a similar app that let you overlay and conform existing 3d models over 2d images. bet this new app shown could be assisted by the former so it could perform the latter if I make sense.

    amazing stuff regardless.

  16. I am so glad, that I found this YouTube channel 😃 it is incredibly interesting to watch! By the way, what job deals with those topics covered by this channel? 🤔

  19. I'm guessing that there is no point into going into a career in 3d modeling and animation now.

    I wonder how much longer it will take until 80% of humans are obsolete and unemployable.

  21. Best channel I have found so far in this year..it's so sad that those kinds of chanels don't exist in german so I could show certain videos to friends and stuff without translating which is pretty hard at this level of complex themes. Keep up the good work

  22. the next step is having it develop a 3d model from pictures of the same object from multiple different angles/lighting conditions, and then extracting a full model from a video!

  23. Man oh man! All of these machine learning papers recently….. It's giving me the idea, realistic or not, that an artificial general intelligence is closer than I thought- By a good margin perhaps….

  27. After watching many of your videos, I think it is reasonable to expect that by the end of the year as similar algorithm will be able to create precise, high resolution 3d models. It blows my mind.

  29. OK if this is possible from a single image, why aren't we getting photogrammetry Deep Learning software that does it in a tenth of what the rest do it, with massively less noise and much more precision? It seems like the perfect match for DL ML.

    Point clouds could be done much faster and the results better. I just want to cryofreeze myself and wake me up pls when this is available

  31. Generally ok when it comes to models for decoration purposes but when it comes to animating, skinning, bending the model or rendering it with a realistic render with raytracing, the outcome would be horrific. Also there's no requirement for scanning simple objects such as cars and chairs which can be easily modeled with polygonal tools but regarding rocks, stones and stuff like that , they can be scanned and then retopologized with a new mesh.

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