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NJU-PCALab/STAR

[ICCV 2025] STAR: Spatial-Temporal Augmentation with Text-to-Video Models for Real-World Video Super-Resolution observed · 2026-08-28

github.com/NJU-PCALab/STAR · Python observed · 2026-08-28

Health v2 · maintenance only

34/100

  • Activity 29
  • Release rhythm 35
  • Longevity 46

Flags: no_releases no_license

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 650
  • days_rel: n/a
  • days_push: 427
  • n_releases_24m: 0

Full methodology

Adoption not part of the score

1495 stars · 87 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

STAR is a research implementation of an ICCV 2025 paper performing real-world video super-resolution using spatial-temporal augmentation with text-to-video diffusion models. It provides inference and training code (I2VGen-XL version) plus online demos on HuggingFace and Colab.

Use cases

  • upscale low-quality real-world videos
  • restore degraded video to high resolution
  • enhance old compressed video footage
  • run diffusion-based video super-resolution
  • reproduce video restoration research results

When to choose

  • you need state-of-the-art real-world video super-resolution
  • you want a diffusion-model-based video restoration pipeline with training code
  • you want to build on published ICCV 2025 research

When to avoid

  • you need a lightweight real-time video upscaler
  • you lack a GPU or cannot run large diffusion models
  • you need a commercially licensed tool (no license is provided)

Facets

library · maturity active

video-processing image-processing deep-learning stable-diffusion computer-vision machine-learning image-processing python video-super-resolution diffusion-models text-to-video iccv-2025 research-code video gpu linux

1 source

Member repositories

RepositoryRoleHealth v2
NJU-PCALab/STARmain34

For agents

markdown · JSON · MCP: product_card(name="NJU-PCALab/STAR")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem