gsplat
LGM
gsplat | LGM | |
---|---|---|
1 | 2 | |
902 | 1,343 | |
8.4% | 13.8% | |
9.3 | 6.6 | |
5 days ago | 2 months ago | |
Cuda | Python | |
Apache License 2.0 | MIT License |
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gsplat
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Level of Gaussians: Real-Time View Synthesis for Square Meters
Cool, but not touching this; no license and requires Inria's proprietary rasterizer.
People should stop basing all of this new research on proprietary software, when we have open source implementations [1][2].
[1] gsplat: https://github.com/nerfstudio-project/gsplat
LGM
- LGM: Large Multi-View Gaussian Model – Create 3D model from text or single image
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GaussianObject: Just Taking Four Images to Get a High-Quality 3D Object
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).
What are some alternatives?
stable-dreamfusion - Text-to-3D & Image-to-3D & Mesh Exportation with NeRF + Diffusion.
GaussianObject - Code for "GaussianObject: Just Taking Four Images to Get A High-Quality 3D Object with Gaussian Splatting"
zero123plus - Code repository for Zero123++: a Single Image to Consistent Multi-view Diffusion Base Model.
dreamgaussian - [ICLR 2024 Oral] Generative Gaussian Splatting for Efficient 3D Content Creation