Open Source Video Upscaler with Temporal Smoothing
Free.ai has launched a self-hosted video upscaler that utilizes Real-ESRGAN technology with temporal smoothing. This tool enhances video quality by upscaling each frame while minimizing flicker, making it a competitive alternative to commercial options. Users can choose to self-host the software or use a hosted API for convenience.
- ▪The Free.ai video upscaler uses Real-ESRGAN to upscale videos by 4× and applies temporal smoothing to reduce flicker.
- ▪A hosted API is available for users who prefer not to self-host the software, allowing easy access to the upscaling service.
- ▪The tool is designed to preserve audio quality while enhancing video detail, making it suitable for various video editing needs.
2 outlets in our directory ran this story, first to last over 9 hours. All of the coverage we found sits in one bucket: centre. That one-sidedness is itself worth noticing.
- ▪ Open Source AI Infrastructure — Ycombinator
Story provenance
Source · retrieval · rights · ranking — open for full record
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Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | GitHub |
| Canonical URL | https://github.com/freeaigit/video-upscaler |
| Publication time | Tue, 28 Apr 2026 02:59:21 +0000 |
| Retrieval time | 2026-04-28T03:27:52.441Z |
| Last seen | 2026-04-28T03:27:52.441Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | 5wetTb2AJ5iy · 2 stories |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Free.ai Video Upscaler Self-hosted Real-ESRGAN x4 video upscaler with temporal smoothing — a free, GPU-backed alternative to Topaz Video Upscaler. Powers the Free.ai video upscaler tool. What it does Takes a video, upscales every frame 4× with Real-ESRGAN, applies a temporal smoothing pass to eliminate frame-to-frame flicker, then re-encodes preserving the source audio. The output is competitive with commercial video upscalers on per-frame detail and temporal coherence. Why temporal smoothing matters Frame-by-frame neural upscalers (the cheap way) introduce high-frequency flicker because each frame is upscaled independently — a slight texture detail in pixel (12,34) might be reconstructed differently by the model on two consecutive frames, producing a shimmer.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.