4 ms·

At this point, this method is only good at reconstructing parts of the scene that are well-photographed. You'll notice that our video for Sacre Coeur has some b

At this point, this method is only good at reconstructing parts of the scene that are well-photographed. You'll notice that our video for Sacre Coeur has some blurry bits, particularly the staircase in front of the Basilica. That's because we learn to reconstruct what was seen, but aren't yet able to imagine what wasn't! Does this work in reconstructing indoor spaces? Give it a shot and find out!

idontevengohere 6y ago
Love how you explained this! And I thought I was the only one using exclamation marks for everything
philipkglass 6y ago
Does this work in reconstructing indoor spaces? Give it a shot and find out! Have you released the code? (Or did you mean I could try re-implementing the work you published from the paper? That's a reasonable response too.) I didn't see a link to source in the github.io page or in the arXiv paper. The only source code link I saw was to https://github.com/bmild/nerf https://github.com/bmild/nerf which I thought was earlier work than this paper.
- duckworthd 6y ago
  Our code is not released yet. If your data is captured without occluders and in RAW format, you don't need the enhancements we propose :). NeRF can do amazing things with clean data!
  - StavrosK 6y ago
    I just saw the NeRF demo video, it's amazing. If its results are this good, why is photogrammetry software not basically perfect yet? It looks like they can generate models with vast amounts of detail.
    - m3at 6y ago
      Not the author (but I read the previous papers and the code), the simple answer is that it's still very costly in processing power. Think a few hours on good hardware for a set of pictures. Note that the results are still very impressive imo, this is still early research phase.
    - duckworthd 6y ago
      NeRF was first published in March! Give us time :)
      - toomuchtodo 6y ago
        Thanks so much for taking the time to do this impromptu AMA. The excitement over the tech is clearly palpable :)

idontevengohere 6y ago

Love how you explained this! And I thought I was the only one using exclamation marks for everything

philipkglass 6y ago

Does this work in reconstructing indoor spaces? Give it a shot and find out! Have you released the code? (Or did you mean I could try re-implementing the work you published from the paper? That's a reasonable response too.) I didn't see a link to source in the github.io page or in the arXiv paper. The only source code link I saw was to https://github.com/bmild/nerf https://github.com/bmild/nerf which I thought was earlier work than this paper.

duckworthd 6y ago
Our code is not released yet. If your data is captured without occluders and in RAW format, you don't need the enhancements we propose :). NeRF can do amazing things with clean data!
- StavrosK 6y ago
  I just saw the NeRF demo video, it's amazing. If its results are this good, why is photogrammetry software not basically perfect yet? It looks like they can generate models with vast amounts of detail.
  - m3at 6y ago
    Not the author (but I read the previous papers and the code), the simple answer is that it's still very costly in processing power. Think a few hours on good hardware for a set of pictures. Note that the results are still very impressive imo, this is still early research phase.
  - duckworthd 6y ago
    NeRF was first published in March! Give us time :)
    - toomuchtodo 6y ago
      Thanks so much for taking the time to do this impromptu AMA. The excitement over the tech is clearly palpable :)