5 AI Video Upscalers to Go From SD to HD and HD to 4K

My grandfather filmed my parents' wedding in 1984 on a VHS camcorder. The footage is 240p, tracked through an 18-inch tube TV, with a scan line running diagonally across every other frame. For 40 years, that was the best version of that memory that existed.

I ran it through Topaz Video AI in 2023. The scan line is mostly gone. The faces are recognizable. You can tell what the flowers on the altar look like. It's not 4K. But it's not the degraded mess it was.

AI video upscaling is technology I genuinely care about in a way I don't feel about most tools in this category. The use cases range from the commercial (fixing drone footage shot in 1080p for a 4K delivery) to the deeply personal (restoring family records that exist nowhere else).

This guide covers the five tools worth knowing, what each one is actually good at, and a practical workflow for the most common restoration scenarios.

How AI Upscaling Actually Works

Traditional upscaling — what your TV does when it shows a 1080p Blu-ray on a 4K display — works by interpolating between existing pixels. The result is a smoother, slightly blurry version of the original. It adds no new information. It just makes the existing low-resolution information bigger.

AI upscaling works fundamentally differently. Neural networks trained on millions of image pairs (low-resolution and high-resolution versions of the same content) learn to predict what the high-resolution version of a low-resolution input probably looks like.

When the model processes your SD video, it's not stretching pixels — it's generating new detail based on statistical patterns learned from the training data. Edges get sharper. Textures become more defined. Faces gain structure that wasn't visible before.

The results aren't perfect because the model is making educated guesses. On organic textures (faces, fabric, foliage), the guesses are usually very good. On text, fine mechanical details, and patterns with regular structure, AI can hallucinate incorrect detail that looks wrong to trained eyes.

For most video content, the improvement is dramatic and the occasional inaccuracy isn't visible unless you're looking for it.

The 5 Tools Worth Using

Topaz Video AI

Topaz Video AI is the professional's choice in this category, and it's not particularly close. The model quality, the feature depth, and the consistency of results for challenging source material set it apart.

The software runs locally on your machine — important both for privacy and for processing speed if you have a capable GPU. The Proteus and Iris models handle most upscaling tasks well; Iris is specifically trained on human faces and produces noticeably better results for portrait and documentary footage.

Beyond upscaling, Topaz Video AI includes frame interpolation (adding frames to increase apparent frame rate), stabilization, noise reduction, and deinterlacing. For archive restoration work, having these tools in one application with the same UI is genuinely efficient.

The processing speed on a mid-range GPU (RTX 3070 or equivalent) is workable for professional use — a 10-minute clip upscaled to 4K takes roughly 45–60 minutes. CPU-only processing is significantly slower, typically 3–5x longer.

The main drawback is cost — $299 for the full license, with an optional annual upgrade plan. For occasional personal use, it's expensive. For professionals using it regularly, it pays for itself quickly.

Our Topaz Video AI review covers the full feature set and model comparisons in detail.

Best for: Professional filmmakers, archivists, anyone restoring important footage who needs the best possible results.

DaVinci Resolve (Super Scale)

DaVinci Resolve is a professional-grade video editor that also happens to include an AI upscaling feature called Super Scale — and the free version of Resolve includes it.

Super Scale uses AI analysis to upscale video resolution within the Resolve timeline. The implementation is less feature-rich than Topaz — you can't choose different upscaling models or fine-tune parameters. But the results are solid, particularly for footage being upscaled for delivery in a professional edit.

For colorists and editors already working in Resolve, Super Scale is the natural choice — no extra software, no export-reimport workflow, no additional cost. The upscaled footage renders with your grade and edit intact.

The limitation is that Super Scale is primarily a timeline tool, not a batch processor. For restoring a library of old footage, the workflow is more cumbersome than Topaz's batch processing approach.

Best for: Editors already working in DaVinci Resolve, professional post-production with mixed-quality footage.

CapCut (AI Enhance)

CapCut's AI enhance feature is the most accessible entry point in this category. It's free, it requires no software installation, and the mobile app makes it usable anywhere.

The enhancement is not as aggressive as Topaz's upscaling models — CapCut enhances clarity, sharpens edges, and reduces noise more than it literally scales resolution. For most short social media clips and YouTube videos, this distinction doesn't matter practically.

Where CapCut's enhance falls short is on heavily degraded archival footage. The neural model is optimized for modern phone video quality rather than old scan artifacts, heavy compression noise, or VHS tracking lines.

For contemporary footage being polished for social media — drone clips, phone video, action camera footage — CapCut's enhancement is entirely sufficient and the price is hard to argue with.

Our CapCut AI features guide covers the full enhancement and editing feature set.

Best for: Casual users, social media content, phone and action camera footage enhancement.

Upscayl

Upscayl is a free, open-source AI upscaling application primarily designed for images but with video support added in recent versions.

For still images, Upscayl is excellent and genuinely competitive with paid alternatives. The video processing is functional but significantly slower than Topaz, with fewer model options and less refined output on challenging video content.

The appeal is obvious: it's free, it's open-source, and it runs entirely locally. For occasional video enhancement where processing time isn't a constraint and you don't need the absolute best quality, Upscayl is a compelling option.

Best for: Budget-conscious users, image-heavy workflows, occasional video enhancement without time pressure.

Runway (AI Upscale)

Runway's cloud-based video enhancement is the most accessible premium option for users without a capable local GPU. Upload your video through the browser, apply the AI enhancement, and download the processed result.

The cloud processing means you don't need a dedicated GPU — Runway handles the compute on their infrastructure. This makes it particularly useful for creators working on older laptops or machines without discrete graphics.

The upscaling quality is good but not at Topaz's level for difficult source material. For typical modern footage going from 1080p to 4K, the difference is minimal. For heavily degraded archival content, Topaz's specialized models produce better results.

Runway charges by processing time rather than a flat subscription, which can add up quickly for long videos or large batches.

Our Runway Gen-2 tutorial covers Runway's broader feature set including generative video capabilities.

Best for: Users without a dedicated GPU, occasional upscaling tasks, cloud-first workflows.

Full Comparison Table

Old Footage Restoration Workflow

Here's the workflow I use for archival footage restoration, tested on everything from VHS family recordings to old film transfers:

Step 1: Assess the source. Before committing processing time, play through the footage and note the specific issues: is it just low resolution, or does it have compression artifacts, interlacing lines, color shifts, noise, or tracking problems? Different problems need different fixes, and addressing them in the wrong order wastes time.

Step 2: Deinterlace first. Interlaced video (common in VHS, old broadcast formats) produces a characteristic comb-like artifact on fast-moving content. Deinterlace before upscaling — doing it after makes the artifacts harder to remove. DaVinci Resolve and Topaz both handle deinterlacing well.

Step 3: Reduce noise before upscaling. Counter-intuitive, but important: upscaling amplifies noise. Clean the noise first (Topaz's denoise models or Resolve's noise reduction), then upscale. Upscaling noisy source material produces sharp, high-resolution noise — which looks terrible.

Step 4: Upscale in Topaz Video AI. Choose the model based on content: Iris for faces and documentary footage, Proteus for general footage with fine-tuning control, Artemis for heavily degraded or heavily compressed source.

Start with a 1–2 minute preview export to evaluate results before committing to a full processing job. Adjust model parameters based on what you see.

Step 5: Color correct and deliver. Upscaled archival footage typically needs color adjustment — old footage is often faded, off-tone, or inconsistent. DaVinci Resolve's color tools are the professional standard here. Basic correction in Premiere Pro or CapCut works for less demanding uses.

Realistic expectations: A clean VHS recording of a well-lit event can be upscaled to look convincingly 1080p. Heavily damaged tape with dropouts and severe noise will improve substantially but won't look like it was shot on a modern camera. Manage expectations accordingly when working with clients or family members.

The 4K Upload Trick for YouTube

This one is worth knowing if you're producing YouTube content at 1080p and want to maximize apparent quality.

YouTube's compression algorithm applies different quality settings to videos uploaded at different resolutions. A 4K upload receives higher bitrate compression settings than a 1080p upload — meaning even the 1080p playback version of a 4K upload looks better than a natively uploaded 1080p video.

This means upscaling a 1080p video to 4K before uploading — even if the source content is 1080p — can improve how YouTube's 1080p version looks to viewers.

The improvement is most noticeable in high-motion content, footage with fine detail (text on screen, complex backgrounds), and any video where compression artifacts are visible in the normal 1080p upload.

Tools for this: CapCut's enhance feature handles this well for shorter videos. For batch processing a library of older YouTube content, DaVinci Resolve with Super Scale in a batch render pipeline is more efficient.

When Upscaling Doesn't Help (And When to Reshoot)

There are source conditions where AI upscaling produces unacceptable results:

Heavy compression blocking. MP4 footage with severe compression artifacts (blocky macro-squares across the image) does not upscale well. The AI interpolates the blocks rather than the original scene content. If the compression blocking is severe enough, reshooting is faster than attempting restoration.

Extreme noise. Footage shot in near-darkness with heavy ISO noise can be improved with noise reduction, but the result after upscaling is often mushy rather than sharp. Footage shot in good lighting with clean signal upscales dramatically better.

Severe physical damage. VHS footage with water damage, mold, or significant physical tape damage produces artifacts that AI models struggle to handle. Physical restoration of the tape (or professional forensic recovery services) is sometimes necessary before digital processing.

Motion blur. AI upscaling adds resolution but cannot add temporal information. Blurry footage caused by camera movement or fast-moving subjects stays blurry at higher resolution — it's just a sharper-looking blur.

For footage that falls into these categories, the honest advice is: if it's important footage, consult a professional restoration service. If it's production footage, reshoot.

For video content that pairs well with AI upscaling workflows — particularly AI-generated video that benefits from quality enhancement — our coverage of Pika Labs review and Sora AI video is relevant context for how generative and enhancement tools can work together.

The external resource worth consulting for archival standards is the Library of Congress's digital preservation guidance (loc.gov/preservation/digital) — particularly useful for anyone working with historically significant footage.

Conclusion

For most content creators, the practical choice is straightforward: CapCut's free enhance for social media content, DaVinci Resolve Super Scale for professional edit workflows, and Topaz Video AI when quality is the priority above all else.

The archival restoration use case — old family films, historical footage, degraded recordings — is where Topaz Video AI's investment makes the most sense. The difference between what these models produce and what traditional upscaling delivers on genuinely old footage is not subtle.

The 4K upload trick for YouTube is worth incorporating into any regular production workflow if you're not already shooting in 4K. The quality improvement is real and the cost (a CapCut export) is nothing.

Whatever your use case, AI upscaling has gotten good enough that the question is no longer "can AI improve this footage?" It's "which tool produces the best results for my specific situation?" The tools above give you the answer to that question across most scenarios you're likely to encounter.

Frequently Asked Questions