LAM vs gaussian-splatting
Gaussian avatar creation and scene reconstruction compared
LAM creates an animatable 3D Gaussian head avatar from one image, while gaussian-splatting reconstructs 3D scenes from multiple images with camera data. LAM focuses on digital humans; gaussian-splatting provides tools for training and inspecting general scene representations.
LAM: Create Animatable 3D Gaussian Avatars from One Image
LAM reconstructs a 3D Gaussian head avatar from a single image and supports animation and rendering across devices. It is aimed at developers building digital humans, especially interactive avatars, and requires model assets and a compatible compute environment for local use.
gaussian-splatting: Reconstruct and Render 3D Scenes in Real Time
The authors’ reference implementation of 3D Gaussian Splatting, which reconstructs scenes from posed images and renders novel viewpoints. It suits graphics and vision researchers and practitioners with CUDA-capable GPUs who need a trainable, interactive scene representation.
| LAM | gaussian-splatting | |
|---|---|---|
| Language | Python | Python |
| License | Apache-2.0 | NOASSERTION |
| Stars | 1.1k | 24.1k |
| Forks | 106 | 3.5k |
| Last analyzed | Oct 3, 2026 | Oct 3, 2026 |
Key differences
- LAM reconstructs a head avatar from a single image; gaussian-splatting trains a scene representation from multiple images and camera data.
- LAM includes inference scripts and a Gradio application, plus hosted demos; gaussian-splatting includes training tools and interactive viewers for inspecting scenes.
- LAM targets avatar and digital-human developers, while gaussian-splatting is aimed at graphics and computer-vision researchers and practitioners.
- Both use Python, but LAM is licensed under Apache-2.0 and gaussian-splatting has a NOASSERTION license.
- LAM local use requires model weights, supporting assets, and compatible CUDA dependencies; gaussian-splatting requires suitable image and camera inputs, CUDA tooling, and a CUDA-capable GPU.
- The supplied project data lists LAM at 1.1k stars and gaussian-splatting at 24.1k stars.
Choose LAM if you…
- need to create an animatable head avatar from one image.
- want to try avatar reconstruction through hosted demos or a Gradio application.
- plan to explore digital-human workflows or export avatars for OpenAvatarChat.
Choose gaussian-splatting if you…
- need to reconstruct a 3D scene from multiple images and camera data.
- want to train and inspect Gaussian scene representations with interactive viewers.
- plan to evaluate novel-view rendering or use a differentiable Gaussian rasterizer in another project.
Compare the numbers side by side, or add more projects
This comparison is generated with AI from the OSRepos analyses of both projects. Always check each project's repository and documentation before choosing.