[HN Gopher] GaussianObject: Just Taking Four Images to Get a Hig...
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GaussianObject: Just Taking Four Images to Get a High-Quality 3D
Object
Author : smusamashah
Score : 98 points
Date : 2024-02-21 13:31 UTC (9 hours ago)
(HTM) web link (gaussianobject.github.io)
(TXT) w3m dump (gaussianobject.github.io)
| Flux159 wrote:
| I wonder how this compares to LGM outputs which also came out
| recently - https://github.com/3DTopia/LGM - specifically LGM
| looks like it's generating the additional viewpoints from text or
| an image and then creating a mesh whereas GaussianObject seems to
| require 4 viewpoints.
|
| We're getting closer to workflows that can generate good 3d
| objects and texture them with diffusion models, there's a bit of
| work in integrating these into existing tooling though - also,
| animations and rigging for characters still seems to be a big
| issue (at least I haven't seen any good 3d generation models that
| can create rigged characters yet).
| jsheard wrote:
| Animation has always been the achilles heel of new 3D
| representations, the first thing you should ask when someone
| claims to have replaced triangles is "how do I animate this?".
| The answer is generally "you can't" and then the technique
| fades into obscurity. A decade ago it was voxels coming to
| replace triangle meshes and that went nowhere.
|
| It is possible to turn a NeRF into a mesh, but the quality of
| the meshes produced is currently so poor that it doesn't really
| get us any closer to being able to animate or edit the model.
| tdudhhu wrote:
| Depends on how you are going to use the result.
|
| This method is great for creating assets. Photogrammetry is
| already used a lot.
|
| The rule for a lot if 3D work is: if it looks good, it is
| good.
|
| But I agree this method won't be suitable for all 3D work.
| jsheard wrote:
| Photogrammetry requires a lot of manual cleanup and
| retopology work, but it's worth the trouble because it
| captures a lot of extremely fine detail which can be baked
| down into textures and applied to the manually refined
| model. It's not really clear to me that NeRFs are producing
| enough detail to warrant that cleanup effort, rather than
| modelling something from scratch.
|
| I would be interested to see a comparison of conventional
| SOTA photogrammetry pipelines versus NeRF techniques
| solving a 3D model from the same set of photos, but these
| papers only ever seem to compare themselves to other NeRF
| papers, rather than the software that the industry is
| already using to solve this exact problem.
| tdudhhu wrote:
| Well again: if it looks good it is good.
|
| When you are not creating assets for games or close-up
| details it can still be very usefull to take a couple of
| pictures of a tree stump and use it in your environment.
| matt3D wrote:
| Also photogrammetry from an industry level.
|
| I work in construction, we take photos of the building in
| situ as a lot of the important elements are encased later
| (eg. Reinforcement inside concrete)
|
| This level of 3D NeRF is great for that as it's much
| easier to parse than a folder full of images.
| regularfry wrote:
| https://github.com/Anttwo/SuGaR looks non-poor to me, but
| I've not had a chance to play with it properly yet.
| zokier wrote:
| There is work ongoing to animate gaussians:
|
| https://www.youtube.com/watch?v=C4IT1gnkaF0 D3GA: Drivable 3D
| Gaussian Avatars
|
| https://www.youtube.com/watch?v=q5hHZrRUV-k Animatable
| Gaussians: Learning Pose-dependent Gaussian Maps for High-
| fidelity Human Avatar Modeling
| jsheard wrote:
| It's something, but I find it difficult to get excited
| about "we trained another NN to perform this specific
| transformation on this specific type of asset". Does it not
| generalize? What are you supposed to do if the NN doesn't
| get it right? It's an inscrutable black box on top of a
| stack of other inscrutable black boxes, which maybe make
| things easy if you hit the happy path but make it
| impossible to reason about the problem if it fails.
|
| I can't say I'm a fan of replacing well defined systems
| with a big blob of weights that nobody really understands.
| spookie wrote:
| Yup, just the fact that topology is often rather poor, you're
| making it impossible to translate motion capture data for a
| lot of things. Facial expressions come to mind.
|
| I understand the reasons for different representations for
| reconstruction, but what we really need is to translate that
| into a mesh that is actually useful.
|
| Its great to have something as a reference, don't get me
| wrong, but we are still far away from even being able to
| discreetly assign materials to the object's various parts.
|
| Another big issue is licensing, most of these are not allowed
| commercially.
| juancn wrote:
| The link is broken for me (may be a transient error),
| alternative: https://github.com/GaussianObject/GaussianObject
| rowanG077 wrote:
| Can you reconstruct a real 3d model from it? What is the
| accuracy?
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