VOID Video Inpainting ComfyUI | Temporal Object Clean-Up Workflow

Erase objects from videos with smooth, consistent scene restoration.

Who it's for: creators who want this pipeline in ComfyUI without assembling nodes from scratch. Not for: one-click results with zero tuning - you still choose inputs, prompts, and settings.

Open preloaded workflow on RunComfy

Open preloaded workflow on RunComfy (browser)

Why RunComfy first
- Fewer missing-node surprises - run the graph in a managed environment before you mirror it locally.
- Quick GPU tryout - useful if your local VRAM or install time is the bottleneck.
- Matches the published JSON - the zip follows the same runnable workflow you can open on RunComfy.

When downloading for local ComfyUI makes sense - you want full control over models on disk, batch scripting, or offline runs.

How to use (local ComfyUI)
1. Load inputs (images/video/audio) in the marked loader nodes.
2. Set prompts, resolution, and seeds; start with a short test run.
3. Export from the Save / Write nodes shown in the graph.

Expectations - First run may pull large weights; cloud runs may require a free RunComfy account.

Overview

This workflow helps you remove unwanted objects from videos with temporal precision and scene consistency. Built on Netflix VOID, it intelligently reconstructs masked regions over consecutive frames. The SAM3 prompt-based system provides accurate object masking for complex interactions. Ideal for editors needing natural-looking video restoration. Achieve clean removals without frame-by-frame cleanup, saving hours in post-production.

Important nodes:

Key nodes in ComfyUI VOID Video Inpainting ComfyUI workflow

SAM3_Detect (#75)

Generates the object mask from a short SAM3 phrase. If the mask is too loose or tight, refine the wording to better describe the target and its context. You can also adjust internal refinement controls to crisp edges when needed. Strong masks make later inpainting more stable.

VOIDInpaintConditioning (#10)

Builds the conditioning bundle from your positive prompt, negative prompt, VAE, frames, and SAM3 mask. The positive prompt should describe the scene that remains; avoid phrasing like “remove X.” Use the negative prompt only when consistent artifacts appear. The resulting latent and conditioning signals feed both passes.

SamplerCustomAdvanced (#49) - Pass 1

Runs VOID sampling for the first pass with random noise. The noise seed controls repeatability; change it when you want a different fill pattern. Keep the sampler and scheduler paired with the Pass 1 UNet. Inspect this pass to validate composition and basic motion before refinement.

VOIDWarpedNoise (#31)

Creates temporally aligned noise using RAFT optical flow computed from Pass 1 frames. This preserves motion cues into Pass 2 and reduces flicker. If motion looks unstable, revisit the mask quality or try a different seed in Pass 1 to generate a better base for warping.

SamplerCustomAdvanced (#35) - Pass 2

Refines the inpainted region starting from warped noise. Use it to lock in textures and stabilize fine details across time. When outputs are already stable, you can skip Pass 2 to save time; otherwise, keep it enabled for final delivery.

ComfySwitchNode (#150) - Skip control

Toggles between Pass 1 and Pass 2 frames for the final output. Use this to A/B check quality or to speed up iterations while you adjust prompts and the SAM3 mask. Turn it off for the definitive VOID Video Inpainting ComfyUI result.

Notes

VOID Video Inpainting ComfyUI | Temporal Object Clean-Up Workflow - see RunComfy page for the latest node requirements.