Restore and upscale any video to 4X and beyond in a single step with ByteDance's revolutionary SeedVR2.
Watch the complete 32-minute deep dive above explaining every parameter and optimization.
🚀 What this workflow does
This workflow implements SeedVR2's groundbreaking one-step video restoration that previously required 15-50 denoising steps. Unlike traditional upscalers that process frames individually (causing flickering), SeedVR2 maintains temporal consistency by processing batches of frames together.
Key features:
One-step processing - 15-50x faster than traditional diffusion upscalers
Unlimited resolution - Tested up to 10x upscaling (limited only by VRAM)
Temporal consistency - No flickering with high batch_size
Alpha channel support - Upscale image sequences by chaining two upscale nodes
BlockSwap enabled - Run 7B parameter models with 16GB VRAM
📚 What You'll learn in the tutorial
Architecture deep dive:
- How Diffusion Adversarial Post-Training achieves single-step inference
- Why GANs + Diffusion = game changer for video restoration
- Understanding the Swin Transformer backbone
Practical implementation:
- Choosing between 3B/7B models and FP8/FP16 precision
- Why batch_size must be high for optimal results
- BlockSwap configuration for limited VRAM (detailed parameter breakdown)
- Memory optimization strategies
Advanced Workflows:
- Processing image sequences with alpha channels
- Multi-GPU command line setup for production pipelines
- Resolution stepping to control detail enhancement
- Dealing with oversharpening on AI-generated content
🛠️ Workflow Includes
- Image & Video upscaling workflow, including image sequences with alpha channel
⚡ Performance notes
- 3B FP8: Fastest, good for previews
- 7B FP16: Best quality, requires BlockSwap on consumer cards
- VAE bottleneck: 95% of processing time is encoding/decoding and the VAE is currently using a fair amount of VRAM.
- Temporal batching: Higher batch_size = better consistency but more VRAM
🎯 Best use cases
✅ Perfect for:
Restoring compressed/heavily degraded footage
Upscaling legacy content
AI-generated video enhancement
⚠️ Consider alternatives for:
Already high-quality footage (may oversharpen)
Limited VRAM
Content requiring subtle enhancement
🔧 Requirements
ComfyUI (latest version)
16GB+ VRAM recommended
ComfyUI-SeedVR2_VideoUpscaler by NumZ: https://github.com/numz/ComfyUI-SeedVR2_VideoUpscaler
ComfyUI-CoCoTools_IO by Conor-Collins: https://github.com/Conor-Collins/ComfyUI-CoCoTools_IO
ComfyUI-VideoHelperSuite by Kosinkadink: https://github.com/Kosinkadink/ComfyUI-VideoHelperSuite
Models auto-download on first use
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Every donation enables us to dedicate more time to research, testing, and sharing knowledge. Thank you for being part of this journey!
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