This comprehensive workflow showcases the latest Wan2.2-Animate 14B model, a groundbreaking unified model for character animation and replacement with holistic movement and expression replication . This workflow...
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This comprehensive workflow showcases the latest Wan2.2-Animate 14B model, a groundbreaking unified model for character animation and replacement with holistic movement and expression replication . This workflow represents the cutting edge of AI video generation, combining pose-guided animation, face replacement, and audio-driven generation in a single, professional-grade workflow.
Credits
Workflow Developer: Jukka Seppänen (kijai)
GitHub: https://github.com/kijai
Creator of ComfyUI-WanVideoWrapper and numerous essential ComfyUI extensions [3][4][5]
Sources
1 sourceSource excerpts
1 excerptSource context: 736 downloads · Type Workflows · Base model Wan Video 2.2 I2V-A14B
Video Content: Riku Sutinen
Instagram: https://www.instagram.com/sutinen.riku/
Professional content creator providing demonstration footage
What is Wan2.2-Animate 14B?
The Wan2.2-Animate 14B model represents the latest advancement in AI video generation technology, specifically designed for character animation and replacement [1]. Unlike previous models, this unified architecture can handle both movement replication and facial expression replacement simultaneously, making it ideal for creating realistic character animations with unprecedented quality and control [1].
Core Workflow Components
Model Architecture
The workflow utilizes the complete Wan2.2-Animate ecosystem:
Primary Model: Wan2.2-Animate-14B-fp8-e4m3fn-scaled-KJ.safetensors [3]
Text Encoder: umt5-xxl-enc-bf16.safetensors for advanced prompt understanding [6]
VAE: Wan2.1-VAE-bf16.safetensors for optimal encoding/decoding [6]
LoRA Support: WanVideo-relight-lora-fp16.safetensors for lighting control [3]
Advanced Input Processing
Reference Image System*
The workflow features a sophisticated reference image processing pipeline that extracts character features and maintains consistency across the entire animation sequence [3]. The ImageResizeKJv2 node ensures proper aspect ratio handling while preserving character integrity.
Pose Control Integration
Using the DWPose preprocessor, the workflow extracts detailed pose keypoints from input videos, enabling precise control over character movement [3]. The FaceMaskFromPoseKeypoints node generates accurate facial regions for targeted animation control.
Audio Synchronization
The workflow includes comprehensive audio processing capabilities through the VHSLoadVideo node, allowing for perfect lip-sync and audio-dri en animation
Professional Quality Feature
Background Masking & Compositing
The workflow employs advanced masking techniques using SAM2 (Segment Anything 2) for precise background separation [3]. The Sam2Segmentation and BlockifyMask nodes ensure clean compositing with professional-grade edge handling.
Multi-Resolution Support
The workflow dynamically handles various resolutions with dedicated width/height management nodes, ensuring optimal quality regardless of input dimensions [3]. The INTConstant nodes provide flexible resolution control (832x480 default).
Context Window Management
Advanced context options enable extended video generation beyond standard frame limits through the WanVideoContextOptions node, supporting up to 81-frame windows with temporal consistency [3].
Technical Specifications
Hardware Requirements
GPU: RTX 4090 or equivalent (24GB VRAM recommended)
Model Size: 14B parameters with FP8 optimization
Memory Optimization: Utilizes scaled FP8 quantization for efficiency [1][7]
Model Performance
Resolution: Up to 832x480 native support
Frame Rate: 16 FPS output with smooth temporal consistency
Animation Length: Configurable from short clips to extended sequences
Processing Speed: Optimized for consumer hardware with professional results
Workflow Structure & Organization
Modular Design
The workflow is organized into five main sections [3]:
Reference Image Processing: Character extraction and preparation
Face Image Generation: Facial feature processing and mask creation
Background Masking: Scene separation and compositing preparation
Model Configuration: Core AI model setup and parameter tuning
Result Generation: Final video compilation and output
Node Architecture
The workflow utilizes advanced node management with GetNode and SetNode architecture for clean organization and parameter passing [3]. This modular approach enables easy customization and troubleshooting while maintaining workflow in egrity.
Advanced Features
Pose-Guided Animation
The DWPose integration provides professional-grade pose detection and control, enabling natural character movement that follows the reference video while maintaining the target character's appearance [3].
Expression Replication
The Wan2.2-Animate model excels at replicating both gross motor movements and subtle facial expressions, creating believable character animations that maintain emotional authenticity [1].
Lighting Control
The integrated LoRA system includes specialized lighting control, allowing for scene-appropriate illumination that matches the target environment while preserving character details [3].
Audio Integration
Full audio pipeline support enables synchronized audio-video generation, perfect for creating talking head videos or music-synchronized animations [3].
Installation & Setup
Required Extensions
ComfyUI-WanVideoWrapper: Primary integration for Wan2.2 models [4]
ComfyUI-KJNodes: Essential utility nodes for workflow functionality [5]
ComfyUI-segment-anything-2: Advanced masking capabilities
ComfyUI-VideoHelperSuite: Video processing and output management
Model Downloads
All required models are automatically managed through the workflow, with direct links to HuggingFace repositories for manual installation if needed [1][6].
Professional Applications
This workflow is ideal for:
Professional video production with character replacement
Rapid prototyping and pre-visualization
High-qualitycharacter animations for platforms
Engaging video presentations with animated characters
Cost-effective character animation for indie productions.
community Impact
This workflow demonstrates the democratization of professional video animation tools, making Hollywood-quality character animation accessible to creators worldwide [1]. The integration with Civitai's platform ensures widespread distribution and collaborative improvement of the workflow [8].
The open-source nature of kijai's work continues to push the boundaries of what's possible in AI video generation, providing the community with cutting-edge tools that were previously available only to major studios [4][5].
Performance Optimization
The FP8 quantization ensures optimal performance on consumer hardware while maintaining professional quality output [7]. The modular architecture allows for selective processing based on available resources, making this workflow accessible across a wide range of hardware configurations.
This represents the pinnacle of current AI video animation technology, combining ease of use with professional-grade results in an accessible ComfyUI workflow.
Remaining hardware or download-size estimates are not available yet.
Requirements
Vision model · 135 B · SAFETENSORS · Unknown
Checkpoint · 129 MB · PT · Unknown
LoRA · 704 MB · SAFETENSOR · Unknown
sam2_hiera_base_plus.safetensors
File unverifiedVision model · Unknown · Sam2 Hiera Base Plus.safetensors
umt5-xxl-enc-bf16.safetensors
Not resolvedCheckpoint · Unknown
VAE · 242 MB · SAFETENSORS · Unknown
Checkpoint · 17.1 GB · SAFETENSORS · fp8 · full · Unknown
WanAnimate_relight_lora_fp16.safetensors
Not resolvedLoRA · Unknown
Checkpoint · 208 MB · PT · Unknown
comfyui_controlnet_aux
PossibleNode pack · Registry
Node pack · Registry
ComfyUI-segment-anything-2
FoundNode pack · Registry
comfyui-videohelpersuite
FoundNode pack · Registry
ComfyUI-WanVideoWrapper
FoundNode pack · Registry