image generation
SinGAN
GAN trained on a single natural image that generates varied samples with the same patch statistics.
Levelmodel
Classimage generation
Parametersnot in the notes
Contextnot in the notes
Released2 May 2019
Opennessunknown
Runs onnot in the notes
Statusactive
Identity
- Developer
- Technion - Israel Institute of Technology, Google
- Family
- not in the notes
- Released
- 2 May 2019 sourcesannouncement page
- Weights published
- –
- Record checked
- 12 Oct 2026
Where this comes from
Developer and dates from the research notes. Release date is the vendor's public announcement; weights date is when open weights were published.
Architecture and Size
- Architecture
- CNN
- Total parameters
- – sources
- Active parameters
- –
- Checkpoint parameters
- –
- Note
- Checkpoints in OpenMMLab MMagic; repository licence Apache-2.0, weight terms not separately stated.
- Context length
- not in the notes
- Input
- image
- Output
- image
Where this comes from
Parameter counts as the developer states them. Where the checkpoint holds a different total, both are shown (register A16).
Openness and Access
- Openness
- unknown
- Licence
- not in the notes sources
- Access routes
- open weights download
Where this comes from
The licence file governs over registry tags and aggregator labels.
Deployment
- Runs on
- not in the notes
- Footprint
- not in the notes
- Runtimes
- not in the notes
Where this comes from
Deployment tiers and runtimes as named in the notes. Footprint is the notes' figure, not a measurement by AURION.
Indonesia
- Indonesian support
- not stated
- Regional languages
- not in the notes
- Jakarta hosting
- unknown
- Languages
- not in the notes
Where this comes from
Indonesia fields are carried on every model; unknown is an allowed value.
Benchmark Results
The notes record no benchmark result for this model.
Lineage
The notes record no lineage for this model.
Industry Use Cases
No industry use case links this model.
Links
ModelSinGANTechnion - Israel Institute of Technology, image generation
SinGANTechnion - Israel Institute of Technology, image generationUse Casesnone recorded
Who Runs Itnone recorded
Organisations 2
Sources
- arxiv.org/abs/1905.01164 https://arxiv.org/abs/1905.01164
- github.com/open-mmlab/mmagic/tree/main/configs/singan https://github.com/open-mmlab/mmagic/tree/main/configs/singan
- arxiv.org/html/1905.01164 https://arxiv.org/html/1905.01164
To cite this page: Project AURION, AI Use-Cases Research & Innovation, "SinGAN", https://aurion.semai.id/models/singan/, records of October 2026.