The framework includes a variational autoencoder (VAE) that maintains a consistent sparse volumetric format across input, latent, and output stages. This unified design markedly improves training efficiency and stability. Direct3D-S2 is trained on publicly available datasets and surpasses state-of-the-art methods in generation quality and efficiency. It enables training at 1024³ resolution with just 8 GPUs, making gigascale 3D generation both practical and accessible.
Direct3D-S2 has a wide range of applications in computer vision, graphics, and robotics. Its ability to generate high-resolution 3D shapes using volumetric representations makes it a valuable tool for various industries, such as architecture, product design, and video production. The model's efficiency and scalability also make it suitable for use in real-time applications, such as 3D reconstruction and tracking.
