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September 29, 2025Open Access

Direct3D-S2: Gigascale 3D Generation Made Easy with Spatial Sparse Attention

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Direct3D-S2 achieves a 3.9x speedup in forward pass operations and a 9.6x speedup in backward pass processes.
The model employs spatial sparse attention, enhancing computation on sparse volumetric data for efficient 3D generation.
Training the model at 1024 resolution is possible with only 8 GPUs, compared to at least 32 GPUs for previous methods.
The integration of a variational autoencoder ensures consistent sparse volumetric formats throughout the model's processes.

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Direct3D-S2 demonstrates superior 3D generation efficiency in spatial sparse volumetric data, implying faster training.

Wu et al. (2025) studied this question.

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