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smthemex / ComfyUI_SparkVSR_SM

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SparkVSR: Interactive Video Super-Resolution via Sparse Keyframe Propagation

18
1
100% credibility
Found Mar 28, 2026 at 18 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

A ComfyUI custom node that enables interactive video super-resolution by propagating details from sparse high-quality keyframes to enhance low-resolution footage.

How It Works

1
🔍 Discover SparkVSR

You hear about SparkVSR, a tool that magically sharpens old videos using just a few clear key moments.

2
📥 Add to ComfyUI

Pop it into your ComfyUI app like adding a new filter – super easy.

3
🧠 Grab the brains

Download the special image enhancers so it knows how to think sharp.

4
📹 Upload your video

Drag in your blurry clip, feeling hopeful for that crisp upgrade.

5
Pick helpers?
✅
Use guides

Select 1-3 sharp moments from your video to inspire the rest.

🚀
Go solo

Let it figure out everything on its own – quick and simple.

6
✨ Hit upscale

Watch as fuzzy footage transforms into stunning high-definition glory.

🎉 Perfect video

Your upgraded clip is ready to share, looking professionally sharp and smooth.

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Star Growth

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AI-Generated Review

What is ComfyUI_SparkVSR_SM?

ComfyUI_SparkVSR_SM integrates SparkVSR into ComfyUI, enabling interactive video super-resolution via sparse keyframe propagation in Python workflows. Upload a low-res video, pick sparse keyframes (like the first frame or every 16th), and it propagates high-res details across the full clip—perfect for upscaling without processing every frame from scratch. Users get tiled, chunked inference for huge videos, with optional single-frame upscaling via PiSASR references.

Why is it gaining traction?

It stands out by making state-of-the-art video super-resolution dead simple in ComfyUI—no custom scripts needed, just drag-and-drop nodes for model loading, ref preprocessing, and sampling with overlap controls. The sparse keyframe approach crushes full-frame alternatives on speed and VRAM for long clips, while ref_guidance_scale dials in fidelity. Developers hook it for quick prototypes since it handles GGUF/safetensors models and auto-pads for VAE compatibility.

Who should use this?

ComfyUI powerusers restoring old footage or enhancing AI-generated videos at 4x scale. Video AI artists needing efficient propagation from hand-picked keyframes without crashing on 1000-frame clips. Python scripters building SR pipelines who want tiling for consumer GPUs.

Verdict

Grab it if you're in ComfyUI and need fast video SR—works out of the box with provided workflows, but at 18 stars and 1.0% credibility, treat as experimental; test small first and watch for GGUF quirks. Solid for tinkering, but production needs more eyes.

(198 words)

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