video generation
vid2vid
NVIDIA video-to-video synthesis that turns segmentation or pose sequences into photorealistic video.
Levelmodel
Classvideo generation
Parametersnot in the notes
Contextnot in the notes
Released20 Aug 2018
Opennessunknown
Runs onnot in the notes
Statusactive
R&D Topics
Identity
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
- –
- Context length
- not in the notes
- Input
- video
- Output
- video
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
DeveloperNVIDIAbig tech, USA
NVIDIAbig tech, USAModelvid2vidNVIDIA, video generation
vid2vidNVIDIA, video generationR&D TopicsVideo Editing and Controllable Video GenerationGenerative Image Modelling Methods (GANs, Diffusion and Image Translation)
Use Casesnone recorded
Who Runs Itnone recorded
Organisations 1
R&D topics 2
Generative Image Modelling Methods (GANs, Diffusion and Image Translation)Core methods for learning to generate or translate images, from GANs and autoencoders to…produced byVideo Editing and Controllable Video GenerationEditing existing video, or steering generation with references, masks, poses or motion mo…produced by
Sources
- arxiv.org/abs/1808.06601 https://arxiv.org/abs/1808.06601
- github.com/NVIDIA/vid2vid https://github.com/NVIDIA/vid2vid
- modelzoo.co/model/vid2vid https://modelzoo.co/model/vid2vid
To cite this page: Project AURION, AI Use-Cases Research & Innovation, "vid2vid", https://aurion.semai.id/models/nvidia-vid2vid/, records of October 2026.