DynVFX: Real-Time Video Augmentation with Dynamic Content Using AI Diffusion Models

DynVFX: Real-Time Video Augmentation with Dynamic Content Using AI Diffusion Models

By Danah Yatim, Rafail Fridman, Omer Bar-Tal, and Tali Dekel
Weizmann Institute of Science
SIGGRAPH Asia 2025

DynVFX is a groundbreaking method for augmenting real-world videos with newly generated dynamic content. This technique allows users to add or modify elements in a video by simply providing a text instruction, resulting in a seamless integration of the new content into the original footage. The system handles complex interactions such as camera motion, occlusions, and dynamic object movements, ensuring that the augmented content looks natural and cohesive.

Technical Overview

• Zero-Shot, Training-Free Framework: DynVFX leverages pre-trained models to achieve its goals without additional training.

  • Text-to-Video Diffusion Model: Synthesizes new content based on user-provided text instructions.
  • Vision Language Model (VLM): Ensures the augmented content is contextually appropriate and detailed.

• Sampling-Based Method for Feature Manipulation:

  • The method manipulates features within the attention mechanism of the diffusion model to accurately localize and integrate the new content.
  • This ensures that the synthesized elements are placed correctly and interact naturally with the existing scene.

Implementation Details

1. Input: A real-world video and a text instruction describing the desired augmentation.
2. Pre-Processing:
   • The input video is analyzed for camera motion, object tracking, and scene segmentation.
   • The text instruction is processed by the VLM to generate a detailed description of the desired content.
3. Content Synthesis:
   • The diffusion model uses the processed text to generate new dynamic elements.
   • These elements are then placed in the video using the attention mechanism to ensure accurate localization and integration.
4. Post-Processing:
   • The augmented frames are blended with the original footage, accounting for occlusions and interactions.
   • The final output is a cohesive video that seamlessly combines the new content with the original scene.

Key Features

• Seamless Integration: The method ensures that the new content blends naturally with the existing video, handling complex scenarios such as camera motion and dynamic object interactions.
• User-Friendly: Users only need to provide a simple text instruction, making the process accessible and easy to use.
• Versatile Applications: DynVFX can be applied to a wide range of edits, from adding new objects to creating complex scene effects.

Benchmarks and Results

DynVFX has been tested on a variety of real-world videos, demonstrating its effectiveness in various scenarios. The method successfully handles:

• Camera Motion: Ensures that the new content moves naturally with the camera.
• Occlusions: Properly places objects behind or in front of existing elements as needed.
• Dynamic Object Interactions: Generates new content that interacts realistically with other moving objects in the scene.

Example Applications

1. Adding New Objects:

   • Input: A video of a city street.
   • Text Instruction: "Add a flying drone."
   • Result: The drone is seamlessly integrated into the footage, flying over the street and interacting with the environment.

2. Creating Scene Effects:

   • Input: A video of a forest.
   • Text Instruction: "Add a magical mist."
   • Result: A realistic mist effect is generated, moving through the trees and enhancing the scene's atmosphere.

3. Modifying Existing Elements:

   • Input: A video of a sports event.
   • Text Instruction: "Change the ball color to blue."
   • Result: The ball in the footage changes color while maintaining its motion and interactions with other elements.

Conclusion

DynVFX represents a significant advancement in video augmentation technology. By combining pre-trained models and a novel sampling-based method, it enables users to add or modify dynamic content in real-world videos with ease and precision. This opens up new possibilities for creative applications in film, advertising, and more.