Jun 12, 2025 · Can the intrinsic Ks be differentiable in the _rasterization function? #727 New issue Open thuanz123

Apr 14, 2025 · Q2. we want depth to have gradients w.r.t all gs. traditional depth test is not differentiable thats the reason.

Jan 9, 2024 · Another way that is much easier to implement, is that after we render the z depth image, we can convert the per-pixel z depth to ray depth using the intrinsic matrix in torch. …

Oct 4, 2024 · First, Thanks for sharing your great work. I have a question about gradient through pose. In simple trainer, pose optimization is used to get gradient from rasterization and …

This function supports a handful of features, similar to the :func:`rasterization` function. .. warning:: This function is currently not differentiable w.r.t. the camera intrinsics `Ks`.

2D multivariate distribution has a different probability related to 1-2-3 sigma The black scatter is a plot of 1000 samples 2D multivariate gaussian distribution. The blue ellipse uses the 3 sigma ...

gsplat is an open-source library for CUDA-accelerated differentiable rasterization of 3D gaussians with Python bindings. It is inspired by the SIGGRAPH paper "3D Gaussian Splatting for Real …

CUDA accelerated rasterization of gaussian splatting - no inplace operations, differentiable now · nerfstudio-project/gsplat@1ac0540

A flattened list of shape [M]. """ image_dims = means2d.shape [:-2] tile_height, tile_width = isect_offsets.shape [-2:] N = means2d.shape [-2] assert transmittances.shape == image_dims …

CUDA accelerated rasterization of gaussian splatting - Comparing nerfstudio-project:b60e917...asrathore-ai:a99c3a3 · nerfstudio-project/gsplat