ByteDance's SeedVR2 on SageMaker AI upscales videos to 4K at scale

As display resolutions climb, organizations grapple with pixelated legacy video content. Traditional upscaling suffers from inconsistent quality and computational limits. ByteDance's SeedVR2, an open-source video restoration model, addresses these challenges when deployed on Amazon SageMaker AI. The solution uses a three-tier AWS architecture defined with AWS CDK: a SecurityStack (VPC, IAM least-privilege, KMS encryption), a DataStack (S3 buckets with versioning and lifecycle policies), and a processing pipeline. Videos uploaded to an input S3 bucket trigger a Lambda function that launches a SageMaker processing job on ml.g5.4xlarge instances, running a custom Docker container with SeedVR2 and ComfyUI for hardware-optimized inference. The upscaled output is saved to another S3 bucket, with CloudWatch for logging.

Use cases span industries. Archives and museums restore historical footage; streaming services upgrade TV shows and movies to 4K. A standout application is upscaling AI-generated videos, which are often created at lower resolutions due to compute costs. SeedVR2 enables a two-stage workflow: rapid prototyping at lower resolutions then enhancing to high quality, reducing time and compute while maintaining modern display standards. The combination of SeedVR2's frame-by-frame analysis and SageMaker's managed scalability means organizations can process large video collections efficiently, avoiding the need to repurchase content in higher resolutions.