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Localrf – Nerf from casual shaky videos

localrf.github.io

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Re: Localrf – Nerf from casual shaky videos

#21
post #20

Can't wait for this stuff to become so good and polished behind a UI, so that I can just point it to a folder of videos and see what comes out.

Check out Luma it's an iPhone app that makes it really easy to create Nerfs and render out videos from them. Although I don't think it handles long paths like this method yet.

https://lumalabs.ai/

Re: Localrf – Nerf from casual shaky videos

#22

nice edit: is this process public? how can i test and try this? on kdenlive? edit 2: https://github.com/facebookresearch/localrf got it but when will it be implemented by kdenlive? any dev here?

It looks like the paper and code for both the original NeRF and this new Localrf method are free and open source, so that bodes well for integration into Kdenlive. In any case, I'm available for contracts ;)

Re: Localrf – Nerf from casual shaky videos

#23
It's interesting how the level of detail improves as the camera gets closer to objects. Specifically the transparency of foliage gets more detailed when getting closer. That makes one think if a multipass version of this thing could use the details it learned later in the timeline to improve the detail level earlier.

Re: Localrf – Nerf from casual shaky videos

#24

My grandmother's farm had to be sold in 2012 after she died. Since my family moved around when I was a kid, but always visited there for holidays, it felt more like home than any other place I lived in. I have extensive videos I recorded in 2006. It'd be wonderful to walk through there again using reconstructions from material I already have. Or maybe not. There's a reason I haven't watched those videos in years. Who…

I think it depends on where you are in life. If your life is good and you feel safe and happy, then looking back can be a nice way to remember your childhood, and possibly rediscover things about yourself you had forgotten. If your life is difficult and you’re not feeling great, looking back at better times can be a painful reminder of things not going the way you’d like. But our lives ebb and flow, and there may be…

Or, to quote Watchmen, "I'm 65 years old. Everyday the future looks a little bit darker. But the past, even the grimy parts of it, well, it just keeps on getting brighter all the time."

Re: Localrf – Nerf from casual shaky videos

#25
What a weird paper. They compare 3D rendering a synthetic camera path against a stock 2D image stabilisation algorithm. Of course, true 3D algorithms will win.

And their main takeaway seems to be that one should do global bundle adjustment for recovering the camera poses ... which I thought has been common knowledge for years and is what pretty much every SfM tool implements.

My TLDR would be: stuff that works well continues to work well even if you use a neural radiance field instead of a point cloud for representing geometry.

Those results look eerily similar to Microsoft's 2016 Hyperlapse paper&software.

Re: Localrf – Nerf from casual shaky videos

#27

When I've got my glasses on, the "Forest" sequences look *wildly* 3D to me. Without my glasses it looks less so but that might be a function of not really being able to focus on stuff closer than about ten metres ;-)

I think what you're getting a demo of there is the bit of our depth perception apparatus that doesn't need stereo pairs to work. Out past a certain distance our brains reconstruct geometry from visual depth cues, and I suspect that the smoothed camera path means that, in contrast to the shaky original video, your eyes are seeing something your inner ears aren't contradicting too much.

Never thought of it that way, but you might very well be right. Something like "my ear isn't shaking, the camera isn't shaking, must be real" ;-)

I wonder if maybe their implementation "fills in the blanks" in the 3D space in the same way our brain does, so it looks "properly 3D" because it's what we're expecting it to look like already?

Re: Localrf – Nerf from casual shaky videos

#28
post #18

Let's say you want to slightly alter the spline the camera of the 3D scene moves along, but the positions/angles would change in such a way there is missing data in the new rendering. How feasible would it be to use current inpainting technologies to fill in the gaps straight in the scene? Would it be better to try to inpaint the rendered frames instead?

You may be interested in GeNVS (https://nvlabs.github.io/genvs/) which combines NeRFs and generative diffusion models.

Re: Localrf – Nerf from casual shaky videos

#29

For those like me who didn't know what NeRF means - Neural Radiance Fields. [1] https://www.matthewtancik.com/nerf [2] https://datagen.tech/guides/synthetic-data/neural-radiance-f...

dang, might the title be corrected to NeRF instead of the toy? ;)
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