Library/vid2vid
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NVIDIA/vid2vid

vid2vid

Pytorch implementation of our method for high-resolution (e.g. 2048x1024) photorealistic video-to-video translation.

Builder

NVIDIA

NVIDIA

NVIDIA • big-tech

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8,718

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Created

Aug 14, 2018

Project creation date

README Summary

NVIDIA's vid2vid is a PyTorch implementation for high-resolution photorealistic video-to-video translation, capable of generating realistic videos at resolutions up to 2048x1024. The method uses advanced deep learning techniques to transform input videos while maintaining temporal consistency and photorealistic quality across frames.

AI Dev Skills

Unmapped

Generative Adversarial NetworksVideo SynthesisConditional Image GenerationTemporal Consistency ModelingHigh-Resolution Image GenerationComputer VisionDeep LearningConvolutional Neural NetworksVideo ProcessingDomain Transfer

Tags

Generative Adversarial NetworksVideo SynthesisConditional Image GenerationTemporal Consistency ModelingHigh-Resolution Image GenerationComputer VisionDeep LearningConvolutional Neural NetworksVideo ProcessingDomain TransferVideo Style TransferAutonomous VehiclesHigh-Resolution SynthesisSelf-hostedMultimodal AIVirtual Environment GenerationVideoEntertainmentRealistic Video Generation from SketchesImageCloud APIGamingRoboticsData Augmentation for Video DatasetsGenerative AIMedia ProductionSemantic Video SynthesisAutonomous Driving SimulationVirtual RealityVideo Content CreationPython

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Updated 3 years ago

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research
Quality
medium
Maturity
research

Categories

Spatial & XRPrimarySafety & AlignmentCoding & Dev ToolsMultimodal AIOther AI / MLGenerative MediaComputer VisionRoboticsFoundation ModelsAI AgentsModel Training

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Developer Platform

Languages

Python100.0%

Timeline

Project created
Aug 14, 2018
Forked
Mar 14, 2026
Your last push
3 years ago
Upstream last push
3 years ago
Tracked since
May 17, 2022

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