2D-Gaussian-Splatting
awesome-3D-gaussian-splatting
| 2D-Gaussian-Splatting | awesome-3D-gaussian-splatting | |
|---|---|---|
| 1 | 2 | |
| 306 | 4,564 | |
| - | - | |
| 6.4 | 9.7 | |
| 30 days ago | 2 days ago | |
| Jupyter Notebook | ||
| MIT License | MIT License |
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2D-Gaussian-Splatting
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[P] 2D Gaussian Splatting a great starting point for people who want to delve deeper
Github : https://github.com/OutofAi/2D-Gaussian-Splatting
awesome-3D-gaussian-splatting
- MrNeRF/awesome-3D-gaussian-splatting: Curated list of papers and resources focused on 3D Gaussian Splatting
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Gsplat: CUDA accelerated rasterization of gaussians with Python bindings
Something close to what you mention is dynamic scene capture, such as this paper: https://dynamic3dgaussians.github.io/
You can manipulate the splats in viewer, kind of similar to a pointcloud, something to the effect of https://twitter.com/parazar/status/1713618668788109357 but there are a bunch around social media.
This has an entrypoint to the research and various projects so far: https://github.com/MrNeRF/awesome-3D-gaussian-splatting
What are some alternatives?
ML-foundations - Machine Learning Foundations: Linear Algebra, Calculus, Statistics & Computer Science
splat - WebGL 3D Gaussian Splat Viewer
gan-vae-pretrained-pytorch - Pretrained GANs + VAEs + classifiers for MNIST/CIFAR in pytorch.
3DGS.cpp - A cross-platform, high performance renderer for Gaussian Splatting using Vulkan Compute. Supports ✅ Windows, Linux, macOS, iOS, and visionOS
SeeAI - Enabling computers to perform NLP on data obtained from advanced computer vision
gaussian_splatting_notes - A detailed formulae explanation on gaussian splatting
TradeMaster - TradeMaster is an open-source platform for quantitative trading empowered by reinforcement learning :fire: :zap: :rainbow:
SuGaR - [CVPR 2024] Official PyTorch implementation of SuGaR: Surface-Aligned Gaussian Splatting for Efficient 3D Mesh Reconstruction and High-Quality Mesh Rendering
pytorch-GAT - My implementation of the original GAT paper (Veličković et al.). I've additionally included the playground.py file for visualizing the Cora dataset, GAT embeddings, an attention mechanism, and entropy histograms. I've supported both Cora (transductive) and PPI (inductive) examples!
ML-Workspace - 🛠 All-in-one web-based IDE specialized for machine learning and data science.
nlp-class - A Natural Language Processing course taught by Professor Ghassemi