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WAN VACE Professional Video-to-Video Complete Workflow

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Workflows

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Published

Jul 10, 2025

Base Model

Wan Video 14B t2v

Hash

AutoV2
CF8A1EA8F1

🎬 Professional Video-to-Video Transformation with WAN VACE

Transform your videos with professional quality using this comprehensive ComfyUI workflow for WAN VACE. This complete pipeline enables seamless video-to-video transformation of long-form videos with advanced features including seamless joining, upscaling, and frame interpolation. Break down lengthy videos into manageable segments, process them individually, and seamlessly combine them back into cohesive, high-quality output.

✨ Key Features

  • Long Video Processing: Handle extended video content by breaking into segments and seamlessly rejoining

  • Complete V2V Pipeline: Full video-to-video transformation workflow

  • Seamless Video Joining: Custom nodes for professional video concatenation without visible transitions

  • Multi-Step Process: Generate → Join → Combine → Upscale → Interpolate

  • Professional Quality: High-quality output with customizable settings

  • Memory Optimization: Low VRAM options for various GPU configurations

  • Batch Processing: Process multiple video segments efficiently

  • Scalable Architecture: Handle videos of any length through intelligent segmentation

📋 Requirements

Essential Model Files

🔴 WAN GGUF Models

🟣 WAN VAE

🟣 WAN Text Encoder

Required Custom Nodes

⚠️ Important: Download these custom nodes from this page (not available in ComfyUI-Manager):

  • seamless_join_video_clips.py

  • combine_video_clips.py

  • Place in: ComfyUI/custom_nodes/

ComfyUI Extensions

⚙️Install these custom notes using the ComfyUI-Manager.

  • ComfyUI-GGUF

  • ComfyUI-VideoHelperSuite

  • ComfyUI-KJNodes

  • ComfyUI-ControlNet-Aux

  • ComfyUI-Frame-Interpolation

  • ComfyUI-Easy-Use

📖 Step-by-Step Guide

Initial Setup

  1. Configure Constants:

    • Width/Height: 576x1024 (9:16 aspect ratio) or match your source video

    • Length: 81 frames per segment

    • Skip Frames: Start with 0

    • Filename Prefix: Set your output folder and prefix

  2. Load Source Materials:

    • Load your source video for restyling

    • Load reference image (ensure similar pose to first video frame)

    • Use SDXL/FLUX with LoRA and ControlNet for best pose matching

Step 1: Generate WAN Videos

  1. Write Prompts:

    • Describe subject, outfit, and background

    • Include action phrases for dynamic results

  2. Generate Video Segments:

    • Click run to generate first 81-frame video segment

    • Increase skip frames by 81 to process next segment

    • Repeat for the entire length of your source video

    • Final segment can be shorter but may have lower quality

    • For long videos: Continue this process until you've covered the full duration

Step 2: Join Videos Seamlessly

  1. Configure Joining:

    • Set folder path to your generated videos

    • Set filename prefix matching your generated files

    • Start with filename suffix = 1

    • Use same prompt from Step 2

  2. Join Process:

    • Run to join first and second videos

    • Increase filename suffix by 1

    • Run to join second and third videos

    • Repeat until all segments are joined

Step 3: Combine, Upscale, and Interpolate

  1. Final Processing Setup:

    • Set folder path to joined videos

    • Keep filename suffix = 1 (constant)

    • Set combine filename for final output

    • Set upscale filename for enhanced version

  2. Execute Final Pipeline:

    • Combine all joined videos

    • Upscale using RealESRGAN (2x scale)

    • Interpolate frames using FILM VFI (2x frame rate)


⚙️ Advanced Settings

Low VRAM Configuration

  • Use the UnetLoaderGGUFDisTorchMultiGPU node for memory optimization

  • Set virtual_vram_gb to 2.0-4.0 for 12GB and lower GPUs

  • Enable use_other_vram for additional memory fallback

Performance Optimization

  • Bypass PathchSageAttentionKJ and ModelPatchTorchSettings if you don't have Triton

  • Adjust batch sizes based on your GPU memory

  • Use appropriate quantization levels for your hardware


🎯 Tips for Best Results

  1. Long Video Strategy: Plan your segmentation approach - 81 frames per segment ensures smooth transitions while maintaining manageable processing chunks

  2. Reference Image Quality: Use high-quality reference images with poses similar to your source video's first frame

  3. Prompt Engineering: Be specific about subject details, clothing, and background elements

  4. Segment Planning: Plan your video segments to maintain narrative continuity across the entire video length

  5. Hardware Considerations: Adjust settings based on your GPU capabilities - longer videos benefit from optimized VRAM settings

  6. Consistency Maintenance: Keep prompts consistent across all segments to ensure visual coherence in the final long video


🩺 Troubleshooting

  • OOM Errors: Increase virtual_vram_gb or reduce batch sizes

  • Missing Nodes: Ensure all custom nodes are properly installed

  • Quality Issues: Check reference image alignment and prompt specificity

  • Processing Slow: Consider using lower quantization models for faster generation


🔧 Custom Nodes Parameter Guide

WanVideoVaceSeamlessJoin Node

This custom node seamlessly joins two video clips with intelligent masking for smooth transitions.

Parameters:

  • mask_last_frames (INT): Number of frames to mask at the end of the first video

    • Default: 0

    • Range: 0-20

    • Use 0 for no masking, 5-10 for subtle blending

  • mask_first_frames (INT): Number of frames to mask at the beginning of the second video

    • Default: 10

    • Range: 0-20

    • Recommended: 10 frames for smooth transitions

  • frame_load_cap (INT): Maximum number of frames to load from each video

    • Default: 81

    • Range: 1-1000

    • Should match your segment length (typically 81)

  • first_video_path (STRING): Full path to the first video file

    • Format: "C:\path\to\video1.mp4"

    • Use absolute paths for reliability

  • second_video_path (STRING): Full path to the second video file

    • Format: "C:\path\to\video2.mp4"

    • Ensure file exists and is accessible

Outputs:

  • image: Combined video frames as image sequence

  • mask: Generated mask for the transition area


CombineVideoClips Node

This node combines multiple video clips into a single continuous sequence with advanced masking options.

Parameters:

  • frame_load_cap (INT): Maximum frames to load per video

    • Default: 81

    • Range: 1-1000

    • Should match your segment frame count

  • mask_last_frames (INT): Frames to mask at the end of each video (except last)

    • Default: 0

    • Range: 0-20

    • Use 0 for clean cuts, 5-10 for fade effects

  • mask_first_frames (INT): Frames to mask at the beginning of each video (except first)

    • Default: 10

    • Range: 0-20

    • Recommended: 10 for smooth transitions

  • first_video_path (STRING): Path to the first video in sequence

    • Base video - typically your original generated video

  • first_joined_video_path (STRING): Path to first seamlessly joined video

    • Result from first WanVideoVaceSeamlessJoin operation

  • second_joined_video_path (STRING): Path to second seamlessly joined video

    • Result from second WanVideoVaceSeamlessJoin operation

  • third_joined_video_path (STRING): Path to third seamlessly joined video

    • Continue pattern for additional segments

  • fourth_joined_video_path (STRING): Path to fourth seamlessly joined video

    • Optional - use if you have this many segments

  • fifth_joined_video_path (STRING): Path to fifth seamlessly joined video

    • Optional - maximum supported segments

  • last_video_path (STRING): Path to the final video in sequence

    • The last generated video segment

Output:

  • image: Combined video sequence as image frames ready for final processing


Parameter Optimization Tips:

For Seamless Joining:

  • Short transitions: mask_first_frames = 5, mask_last_frames = 0

  • Smooth blending: mask_first_frames = 10, mask_last_frames = 5

  • Long crossfades: mask_first_frames = 15, mask_last_frames = 10

For File Paths:

  • Ensure all video files exist before running

  • Use consistent naming conventions for easier batch processing

Frame Count Considerations:

  • Set frame_load_cap to match your segment length (usually 81)

  • Smaller values may truncate longer segments


This workflow provides professional-grade video transformation capabilities with comprehensive control over the entire pipeline from generation to final output.