Comment by spyder
1 day ago
Correct me if I'm wrong but looking at the video this just looks like a 3D point cloud using equal-sized "gaussians" (soft spheres) for each pixel, that's why it looks still pixelated especially at the edges. Even when it's low resolution the real gaussian splatting artifacts look different with spikes an soft blobs at the lower resolution parts. So this is not really doing the same as a real gaussian splatting of combining different sized view-dependent elliptic gaussians splats to reconstruct the scene and also this doesn't seem to reproduce the radiance field as the real gaussian splatting does.
I had to make a lot of concessions to make this work in real-time. There is no way that I know to replicate the fidelity of "actual" Gaussian splatting training process within the 33ms frame budget.
However, I have not baked in the size or orientation into the system. Those are "chosen" by the neural net based on the input RGBD frames. The view dependent effects are also "chosen" by the neural net, but not through an explicit radiance field. If you run the application and zoom in, you will be able to see the splats of different sizes pointing in different directions. The system as limited ability to re-adjust the positions and sizes due to the compute budget leading to the pixelated effect.
I've uploaded a screenshot from LiveSplat where I zoomed in a lot on a piece of fabric. You can see that there is actually a lot of diversity in the shape, orientation, and opacity of the Gaussians produced [1].
[1] https://imgur.com/a/QXxCakM