v1.0.0
A Major Update to V1.0.0
-
Comparing to the official implementation, gsplat enables up to 4x less training memory footprint, and up to 2x less training time on Mip-NeRF 360 captures, and potential more on larger scenes.
-
Support extremely large scene rendering, which is magnitudes faster than the official CUDA backend diff-gaussian-rasterization.
-
Extra features, including batch rasterization, N-D feature rendering (faster), depth rendering, sparse gradient etc.