Mastering Video-to-Video Translation: A Deep Dive into Wan2.1 VACE Model and ComfyUI
Unlock AI-powered video translation with Wan2.1 VACE Model! Discover a workflow that enhances each frame, controls depth, and optimizes generation. Learn how to leverage this innovative technology and transform your video content today!
- Use Case
- Video
- Best For
- Video
- Models
- FluxWan2.1Controlnet
- Key Nodes
- Controlnet
- VRAM
- Low VRAM (≤8GB)
- Reading Time
- 3 min
Workflow Overview
Unlock AI-powered video translation with Wan2.1 VACE Model! Discover a workflow that enhances each frame, controls depth, and optimizes generation. Learn how to leverage this innovative technology and transform your video content today!
Content type: Workflow
Primary intent: Download
Required Models
- Flux
- Wan2.1
- Controlnet
Required Nodes
- Controlnet
Setup Notes
- Install the required models before opening the workflow template.
- Recommended hardware: Low VRAM (≤8GB).
1. Workflow Overview
This workflow uses Wan2.1 VACE Model for Video-to-Video translation, featuring:
Frame Reprocessing: Enhances each frame via AI model
Depth Control: Uses
DepthAnythingfor spatial consistencyStart/End Frame Guidance: Ensures temporal coherence
Flux Optimization: Improves generation stability
2. Core Models
Model Name | Function | Path |
|---|---|---|
VACE-Wan2.1-1.3B-Preview.safetensors | Main video translation model |
|
wan_2.1_vae.safetensors | Video VAE encoder | Same as above |
depth_anything_vitl14.pth | Depth map generator |
|
flux1-dev-fp8.safetensors | Flux optimization model |
|
3. Key Components
Node Name | Function | Installation |
|---|---|---|
WanVideoVACEEncode | Encodes video frames | Install |
DepthAnythingPreprocessor | Generates depth maps | Install |
FluxGuidance | Stabilizes generation | Built-in (requires Flux model) |
VHS_VideoCombine | Renders final video | Install |
4. Workflow Structure
Group 1: Load Models
Loads Wan2.1 VACE, VAE, and T5 text encoder
Group 2: First Frame Reprocessing
Generates depth map from input video’s first frame
Applies
FluxGuidancefor optimized rendering
Group 3: VACE Video Generation
Guided by start/end frames and depth video
Parameters:
Resolution: 512x768 (adjustable)
Frame rate: 16fps (via
VHS_VideoCombine)
Group 4: Video Export
Output: MP4 (H.264, CRF=19)
5. Inputs & Outputs
Required Inputs:
Source video (e.g.,
bc78b00a0e5776429eae83cf6aedc8d294f3031eb601476ecd3974bec50c0559.mp4)Prompt (e.g., "Beautiful girl dancing")
Final Output:
Reprocessed MP4 video (e.g.,
AnimateDiff_00003.mp4)
6. Notes
⚠️ VRAM Requirement: Minimum 16GB (24GB+ recommended)
💡 Model Setup:
Ensure Wan2.1 VACE models are in correct paths
depth_anythingmodel auto-downloads on first run (~1.5GB)
🔧 Tuning Tips:
Adjust
denoise=1inKSamplerfor reprocessing strengthModify
40inFluxGuidancefor detail/stability trade-off