VaeDecodeShapeTrellis - ComfyUI Built-in Node Documentation

This node decodes Trellis2 shape latent representations into a 3D mesh. It uses a VAE to convert sparse shape latent data into mesh geometry and also outputs shape subdivision data generated during decoding. The node supports both single and batched latent inputs and automatically adjusts the mesh orientation to the expected coordinate frame.

Inputs

Parameter	Description	Data Type	Required	Range
`samples`	The latent samples to decode, including the sample tensor and sparse coordinate data. The latent dictionary may also contain optional fields: `coord_counts` for batched shapes, `coord_resolution` to control mesh resolution, and `model_frame` for coordinate orientation.	LATENT	Yes	None
`vae`	The VAE model used to decode the shape latent into a mesh.	VAE	Yes	None

Notes on `samples`

The samples input is a latent dictionary that must contain the samples tensor and the coords sparse coordinates.
If coord_counts is present, it must be a 1D tensor of non-negative integers, and the sum of all counts must equal the total number of coordinate rows. Each count represents one shape in the batch.
If coord_resolution is provided, the mesh resolution is calculated as coord_resolution * 16. Otherwise, the VAE’s built-in resolution buffer is used (default value: 1024).
If model_frame is set to "z_up", the decoded mesh vertices are rotated from a Z-up coordinate system to the Y-up convention used by glTF. The default value is "y_up".

Outputs

Output Name	Description	Data Type
`mesh`	The decoded 3D mesh, containing vertex positions and face indices.	MESH
`shape_subdivides`	Shape subdivision data produced at each stage of the decoding process.	SHAPE_SUBDIVIDES

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​Inputs

​Notes on samples

​Outputs

Inputs

Notes on `samples`

Outputs