A Major Update to V1.0.0
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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.
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Support extremely large scene rendering, which is magnitudes faster than the official CUDA backend diff-gaussian-rasterization.
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Extra features, including batch rasterization, N-D feature rendering (faster), depth rendering, sparse gradient etc.