AI image tools

V-Express

Generate avatar video controlled by reference images, audio, and V-Kps sequences.

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V-Express is an avatar video generation model developed by Tencent AI Lab that balances different control signals through a series of progressive discard operations, enabling the generated video to simultaneously consider pose, input image and audio. The model is especially optimized for situations where the audio signal is weak, solving the challenge of generating avatar videos with varying control signal strength.
V-Express
https://pic.chinaz.com/ai/2024/05/24052805315584550374.jpg
Stakeholders:
V-Express is suitable for developers and researchers who need to generate lifelike avatar videos, especially those professionals who focus on human-computer interaction, virtual assistants, gaming and entertainment. It can help them create virtual characters that resemble real people and enhance the user experience.
Usage Scenario Examples:

  • Generate virtual news anchors that resemble specific people.
  • Create virtual teachers for online education platforms.
  • In game development, generate realistic dialogue animations for non-player characters.

The features of the tool:

  • Controlled generation using the build model enhancement adapter.
  • Balancing different control signals through progressive discard operations.
  • Especially optimized for weak audio signals.
  • Supports the generation of speaking videos consistent with a given video.
  • Can generate vivid mouth movements for fixed faces.
  • Generate lip movements with slight facial movements.
  • Provide parameter adjustment to suit different input conditions.
  • English audio is supported, other languages have not been tested in detail.

Steps for Use:

  • Download the required model file.
  • Prepare reference images, audio, and V-Klis sequences.
  • The appropriate redirection strategy is selected according to the similarity between the target video and the reference image.
  • Run the demo script and enter necessary parameters, such as reference image path and audio path.
  • Adjust the reference_attention_weight and audio_attention_weight parameters as needed.
  • Generate and view the output avatar video.
  • Further adjust parameters based on feedback to optimize the generation effect.

Tool’s Tabs: Avatar video generation, artificial intelligence

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