VOIDWarpedNoise - ComfyUI Built-in Node Documentation

Complete documentation for the VOIDWarpedNoise node in ComfyUI. Learn its inputs, outputs, parameters and usage.

Overview

Generates temporally-correlated noise for the second pass of the VOID video refinement process. It takes the output video from Pass 1 and warps Gaussian noise along optical flow vectors, creating noise that moves consistently with the video content. This warped noise is used as the starting latent for Pass 2, which improves temporal consistency in the final output.

Inputs

Parameter	Description	Data Type	Required	Range
optical_flow	Optical flow model from OpticalFlowLoader (RAFT-large).	OPTICAL_FLOW	Yes	-
video	Pass 1 output video frames [T, H, W, 3].	IMAGE	Yes	-
width	Width of the output latent (default: 672).	INT	Yes	16 to MAX_RESOLUTION (step 8)
height	Height of the output latent (default: 384).	INT	Yes	16 to MAX_RESOLUTION (step 8)
length	Number of pixel frames. Rounded down to make latent_t even (patch_size_t=2 requirement), e.g. 49 → 45 (default: 45).	INT	Yes	1 to MAX_RESOLUTION (step 1)
batch_size	Number of identical noise sequences to generate (default: 1).	INT	Yes	1 to 64

Note on length parameter: The length value is automatically rounded down to the nearest valid value that produces an even latent_t dimension. This is required by the CogVideoX-Fun-V1.5 model’s patch_size_t=2 constraint. A warning is logged when rounding occurs.

Outputs

Output Name	Description	Data Type
warped_noise	A 5D tensor (B, C, T, H, W) containing optical-flow warped Gaussian noise, ready for use as the initial latent in VOID Pass 2.	LATENT

This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! Edit on GitHub

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