video-upscale
Upscale and restore video in ComfyUI — both the quick local path (per-frame ESRGAN like 4x_foolhardy_Remacri via ImageUpscaleWithModel + 4x→2x supersample, with its temporal-flicker tradeoff) and temporal-aware super-resolution (SeedVR2, the newer FlashVSR) with the downscale-first restore pipeline; RIFE/FILM frame interpolation via the BUILT-IN ComfyUI 0.26 FrameInterpolate (rife_v4.26 in models/frame_interpolation/) or the ComfyUI-Frame-Interpolation pack; 2x/4x scaling, VRAM tiers, VHS encode. Captures the classic downscale→SeedVR2→RIFE recipe and the current 2026 recommendation.
npx skills add majiayu000/claude-skill-registry --skill video-upscale --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Video Upscaling & Restoration ## Overview "Upscaling video" in ComfyUI splits into three jobs, and the quality win comes from doing them in the right order: 1. **Spatial restore + upscale** — a *temporal-aware* model that increases resolution **and** cleans compression blocks, blur, and AI-gen mush while keeping frames consistent over time. This is the part a plain image upscaler (ESRGAN, UltimateSDUpscale per-frame) does badly — per-frame upscalers **flicker** because each frame is sharpened independently. Use a video model. 2. **Frame interpolation (VFI)** — synthesize in-between frames to raise fps (e.g. 24→48/60) for smooth motion. Do this **after** the spatial pass. 3. **Encode** — mux frames (+ original audio) back to an MP4. The two leading temporal restorers in 2026 are **SeedVR2** (diffusion-transformer restorer, the proven workhorse) and **FlashVSR** (newer one-step streaming VSR, faster). Frame interpolation is **RIFE** (or FILM) via **ComfyUI-Frame-Interpolation**. > ⚠️ Verification note: every node/pack/model name below was confirmed against the > GitHub repos and the ComfyUI registry / Manager as of June 2026. Where a name is > approximate or version-dependent it is
- Overview
- ⭐ Recommended current pipeline (2026)
- Node-graph sketch
- Why downscale FIRST (the load-bearing trick)
- Quick local path (no downloads) — per-frame ESRGAN + built-in RIFE
- SeedVR2 (recommended restore stage)
- FlashVSR (newer SOTA — faster restore stage)
- Frame interpolation (VFI)
- Built-in (ComfyUI 0.26+) — PREFER this, no custom node needed
- Custom node (more methods / pre-0.26 ComfyUI)
- About "RIFE 56"
- 2x vs 4x
- VRAM tiers
- Gotchas
What does the video-upscale skill do?
Upscale and restore video in ComfyUI — both the quick local path (per-frame ESRGAN like 4x_foolhardy_Remacri via ImageUpscaleWithModel + 4x→2x supersample, with its temporal-flicker tradeoff) and temporal-aware super-resolution (SeedVR2, the newer FlashVSR) with the downscale-first restore pipeline; RIFE/FILM frame interpolation via the BUILT-IN ComfyUI 0.26 FrameInterpolate (rife_v4.26 in models/frame_interpolation/) or the ComfyUI-Frame-Interpolation pack; 2x/4x scaling, VRAM tiers, VHS encode. Captures the classic downscale→SeedVR2→RIFE recipe and the current 2026 recommendation.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill video-upscale --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.