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SMERF: Streamable Memory Efficient Radiance Fields

smerf-3d.github.io

41–50 of 152 posts

Re: SMERF: Streamable Memory Efficient Radiance Fields

#41

Im not sure why this demo runs so horribly in Firefox but not other browsers..anyone else having this?

Runs pretty well (20-100 fps depending on the scene) for me on both Firefox 120.1.1 on Android 14 (Pixel 7; smartphone preset) and Firefox 120.0.1 on Fedora 39 (R7 5800, 64 GB memory, RX 6600 XT; 1440p; desktop preset).

Re: SMERF: Streamable Memory Efficient Radiance Fields

#42
What I'm seeing from all of these things is very accurate single navigable 3D images.

What I haven't seen anything of is feature and object detection, blocking and extraction.

Hopefully a more efficient and streamable codec necessitates the sort of structure that lends itself more easily to analysis.

Re: SMERF: Streamable Memory Efficient Radiance Fields

#43

Wow. Some questions: Take for instance the fulllivingroom demo. (I prefer fps mode.) 1) How many images are input? 2) How long does it take to compute these models? 3) How long does it take to prepare these models for this browser, with all levels, etc? 4) Have you tried this in VR yet?

Glad you liked our work!

1) Around 100-150 if memory serves. This scene is part of the mip-NeRF 360 benchmark, which you can download from the corresponding project website: https://jonbarron.info/mipnerf360/

2) Between 12 and 48 hours, depending on the scene. We train on 8x V100s or 16x A100s.

3) The time for preparing assets is included in 2). I don't have a breakdown for you, but it's something like 50/50.

4) Nope! A keen hacker might be able to do this themselves by editing the JavaScript code. Open your browser's DevTools and have a look -- the code is all there!

Re: SMERF: Streamable Memory Efficient Radiance Fields

#44

When might we see this in consumer VR? I'm surprised we don't already but I was suspecting it was a computation constraint. Does this relieve the computation constraint enough to run on Quest 2/3? Is there something else that would prevent binocular use?

I can't predict the future, but I imagine soon: all of the tools are there. The reason we didn't develop for VR is actually simpler than you'd think: we just don't have the developer time! At the end of the day, only a handful of people actively wrote code for this project.

Re: SMERF: Streamable Memory Efficient Radiance Fields

#47

Great work!! Question for the authors, are there opportunities, where they exist, to not use optimization or tuning methods for reconstructing a model of a scene? We are refining efficient ways of rendering a view of a scene from these models but the scenes remain static. The scenes also take a while to reconstruct too. Can we still achieve the great look and details of RF and GS without paying for an expensive recon…

> Are there opportunities, where they exist, to not use optimization or tuning methods for reconstructing a model of a scene?

If you know a way, let me know! Every system I'm aware of involves optimization in one way or another, from COLMAP to 3D Gaussian Splatting to Instant NGP and more. Optimization is a powerful workhorse that gives us a far wider range of models than a direct solver ever could. > Can we still achieve the great look and details of RF and GS without paying for an expensive reconstruction per instance of the scene?

In the future I hope so. We don't have a convincing way to generate 3D scenes yet, but given the progress in 2D, I think it's only a matter of time.

> Are there ways of greedily reconstructing a scene with traditional CG methods into these new representations now that they are fast to render?

Not that I'm aware of! If there were, I think these works should be on the front page instead of SMERF.

Re: SMERF: Streamable Memory Efficient Radiance Fields

#48

Is there a relatively easy way to apply these kinds of techniques (either NeRFs or gaussian splats) to larger environments even if it's lower precision? Like say small towns/a few blocks worth of env.

In principle, there's no reason you can't fit multiple City blocks at the same time with Instant NGP on a regular desktop. The challenge is in estimating the camera and lens parameters over such a large space. I expect such a reconstruction to be quite fuzzy given the low space resolution.
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