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"Building rome in a day" and the "Photo tourism" papers were seminal works but you're not really making a serious argument if you are claiming them to be equiva

"Building rome in a day" and the "Photo tourism" papers were seminal works but you're not really making a serious argument if you are claiming them to be equivalent prior art to this. I get it, artificial neural nets make everything easy and boring...back in the day when you had to solve difficult linear algebra problems by hand and tweak descriptor matching thresholds for ages...those were the good old glory days of computer vision. ;)

CyberDildonics 6y ago
I think you have an exceptionally warped idea of how manual photosynth was, or maybe you aren't familiar with it at all. https://youtu.be/p16frKJLVi0?t=32 https://youtu.be/p16frKJLVi0?t=32 The core idea is placing pixels in 3D space, in this case by figuring out the transform of the projections of each image. This reconstructs a field by taking into account the direction each color is coming from, but the difficult part is getting that information in the first place, which photosynth already did. This paper seems to be organizing that data into a network while claiming that the entire capability and result is new.
- deleted 6y ago
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- teraflop 6y ago
  The NeRF-W paper is definitely not claiming that the entire capability is novel. The authors even cite the original Photo Tourism paper in the "Related Work" section. The introduction explains what makes their approach different: > The Neural Radiance Fields (NeRF) approach [21] implicitly models the radiance field and density of a scene within the weights of a neural network. Direct volume rendering is then used to synthesize new views, demonstrating a heretofore unprecedented level of fidelity on a range of challenging scenes. Reconstructing camera positions and sparse point clouds is not really the "difficult part"; it's been a fairly well-understood problem for more than a decade, as you point out. Generating high-quality images without obtrusive artifacts is a much harder problem, and Photosynth didn't even try to solve it.
  - CyberDildonics 6y ago
    > Generating high-quality images without obtrusive artifacts is a much harder problem, and Photosynth didn't even try to solve it. That's not really true, there are lots of ways to blend the points/pixels/images together from different viewpoints, including the illumination changing - this looks like more of a refinement in compression/volumetric representation instead of generating geometry and having view dependent textures or some other technique. You can see in the video that some things like the water shift as the view changes in a very soft way, and some things end up represented with more transparency. The results look good, but it might accurate to say that the article is way off in its claims instead of the paper, although the paper fails to mention photosynth as a citation as far as I could see.
    - teraflop 6y ago
      > That's not really true, there are lots of ways to blend the points/pixels/images together from different viewpoints Of course there are, but (as far as I recall) Photosynth didn't use any of them; it only projected the original images on top of a point cloud. In any case, that's kind of my point; the rendering step is where the interesting research has been happening, not the camera pose reconstruction process which is trivially easy in comparison. > although the paper fails to mention photosynth as a citation as far as I could see. Photosynth was Microsoft's implementation of the same technology that was described in the "Photo Tourism" paper from 2006, which the NeRF-W paper does cite. Naturally, it makes more sense for other researchers work to refer to the original academic literature rather than the commercialized product.

CyberDildonics 6y ago

I think you have an exceptionally warped idea of how manual photosynth was, or maybe you aren't familiar with it at all. https://youtu.be/p16frKJLVi0?t=32 https://youtu.be/p16frKJLVi0?t=32 The core idea is placing pixels in 3D space, in this case by figuring out the transform of the projections of each image. This reconstructs a field by taking into account the direction each color is coming from, but the difficult part is getting that information in the first place, which photosynth already did. This paper seems to be organizing that data into a network while claiming that the entire capability and result is new.

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teraflop 6y ago
The NeRF-W paper is definitely not claiming that the entire capability is novel. The authors even cite the original Photo Tourism paper in the "Related Work" section. The introduction explains what makes their approach different: > The Neural Radiance Fields (NeRF) approach [21] implicitly models the radiance field and density of a scene within the weights of a neural network. Direct volume rendering is then used to synthesize new views, demonstrating a heretofore unprecedented level of fidelity on a range of challenging scenes. Reconstructing camera positions and sparse point clouds is not really the "difficult part"; it's been a fairly well-understood problem for more than a decade, as you point out. Generating high-quality images without obtrusive artifacts is a much harder problem, and Photosynth didn't even try to solve it.
- CyberDildonics 6y ago
  > Generating high-quality images without obtrusive artifacts is a much harder problem, and Photosynth didn't even try to solve it. That's not really true, there are lots of ways to blend the points/pixels/images together from different viewpoints, including the illumination changing - this looks like more of a refinement in compression/volumetric representation instead of generating geometry and having view dependent textures or some other technique. You can see in the video that some things like the water shift as the view changes in a very soft way, and some things end up represented with more transparency. The results look good, but it might accurate to say that the article is way off in its claims instead of the paper, although the paper fails to mention photosynth as a citation as far as I could see.
  - teraflop 6y ago
    > That's not really true, there are lots of ways to blend the points/pixels/images together from different viewpoints Of course there are, but (as far as I recall) Photosynth didn't use any of them; it only projected the original images on top of a point cloud. In any case, that's kind of my point; the rendering step is where the interesting research has been happening, not the camera pose reconstruction process which is trivially easy in comparison. > although the paper fails to mention photosynth as a citation as far as I could see. Photosynth was Microsoft's implementation of the same technology that was described in the "Photo Tourism" paper from 2006, which the NeRF-W paper does cite. Naturally, it makes more sense for other researchers work to refer to the original academic literature rather than the commercialized product.