SC-VAE is the sparse compression autoencoder in TRELLIS.2 that maps O-Voxel data to and from compact structured latents.
- Role
- Encode and decode latents
- Data
- Sparse 3D structure and attributes
- Spatial downsampling
- 16× in TRELLIS.2
- Type
- Variational autoencoder
Encode, generate, decode
The encoder compresses structured 3D data; generative models operate in that latent space; the decoder reconstructs shape or texture information for asset export.
Compression is a design tradeoff
A compact latent makes large-scale generation practical, while the autoencoder design determines which geometric and material details survive reconstruction.