thunil/TecoGAN
This repo contains source code and materials for the TEmporally COherent GAN SIGGRAPH project. observed · 2026-08-28
Health v2 · maintenance only
32/100
- Activity 0
- Release rhythm 35
- Longevity 100
Flags: no_releases
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 2734
- days_rel: n/a
- days_push: 1112
- n_releases_24m: 0
Adoption not part of the score
6141 stars · 1131 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded
TecoGAN is the official source code for a temporally coherent GAN for video super-resolution, published at SIGGRAPH/ACM TOG. It includes inference, training, evaluation metrics, and pre-trained models built on TensorFlow.
Use cases
- upscale low-resolution videos with AI
- generate temporally coherent video super-resolution
- train a GAN for video enhancement
- evaluate video super-resolution with temporal metrics
- download pretrained video upscaling models
When to choose
- you need research-grade video super-resolution with temporal coherence
- you want to reproduce or extend the TecoGAN paper
- you have an Nvidia GPU and TensorFlow setup
When to avoid
- you need a simple production-ready video upscaler with easy installation
- you cannot use TensorFlow 1.x or an Nvidia GPU
- you need active development or recent feature updates
Facets
library · maturity maintenance
machine-learning deep-learning video-processing image-processing computer-vision deep-learning image-processing python video-super-resolution gan tensorflow temporally-coherent pretrained-models research-code video linux gpu
1 source
- readme: https://github.com/thunil/TecoGAN · fetched 2026-08-28 · 7ece8acc342f
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| thunil/TecoGAN | main | 32 |
For agents
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem