Turn low-res clips into sharp, natural HD videos fast.

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 transform standard or low-resolution videos into crisp, detailed visuals ready for high-definition distribution. With minimal setup, you can restore fine detail, elevate clarity, and preserve smooth motion. Ideal for improving archival footage or refining AI video outputs, it ensures results that look natural and professional. The process is fast and reliable, designed to optimize each frame for superior texture and definition. Upgrade your footage effortlessly with this intelligent video enhancement workflow.

Important nodes:

Key nodes in ComfyUI Easy Video Upscaler for Footage workflow

VHS_LoadVideo (#130)

Loads the input clip and exposes images, frame count and a video_info blob. If you intend to process just a portion, limit the frame load in the node and align “Frames per Iteration” accordingly. Keeping loader and batch settings in sync prevents stutter or gaps when batches are stitched.

ImageUpscaleWithModel (#303)

Applies RealESRGAN for a quick, artifact-resistant size boost prior to diffusion. Use it to reach or approach your target resolution before refinement so the WAN pass can focus on texture and fine detail instead of large-scale resizing. If your source already matches target size, you can still keep this stage for denoising and structure reinforcement.

UltimateSDUpscaleNoUpscale (#126)

Runs the WAN diffusion refinement in tiles with seam fixing and optional tiled decode to preserve global structure. The few controls that matter here are the sampler steps, denoise strength and seam-related options; higher steps and denoise produce a more assertive look, while lower settings hew closer to your original frames. When you enable high quality in the Settings group, this node automatically adjusts step depth.

WanVideoNAG (#115) and ModelSamplingSD3 (#419)

This pair hooks the WAN model into the sampler and exposes a creativity shift. Lower creativity keeps the output close to the input with gentle enhancement, while higher values add more generative texture and can invent details. For documentary, interviews or archival work, prefer conservative values; for synthetic or AI-originated clips, you can push a bit further.

ImageBatchJoinWithTransition (#244)

Blends the tail of one batch with the head of the next to hide stitch marks. Increase the number of transitioning frames when you notice luminance or texture jumps, and reduce it for faster runs when scenes are uniform. This is the main lever that keeps the Easy Video Upscaler for Footage pipeline seamless on long timelines.

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Notes

Easy Video Upscaler for Footage in ComfyUI | HD Detail Restoration — see RunComfy page for the latest node requirements.