AniPortrait
Maintainer: ZJYang
98
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| Property | Value |
|---|---|
| Run this model | Run on HuggingFace |
| API spec | View on HuggingFace |
| Github link | No Github link provided |
| Paper link | No paper link provided |
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Model overview
AniPortrait is a novel framework that can animate any portrait image by using a segment of audio or another human video. It was developed by researchers from Tencent Games Zhiji and Tencent. The model builds on similar work in audio-driven portrait animation, such as aniportrait-vid2vid and video-retalking. However, AniPortrait aims to produce more photorealistic results compared to previous methods.
Model inputs and outputs
AniPortrait takes a static portrait image and an audio clip or video of a person speaking as inputs. It then generates an animated version of the portrait that synchronizes the facial movements and expressions to the provided audio or video.
Inputs
- Portrait image
- Audio clip or video of a person speaking
Outputs
- Animated portrait video synchronized with the input audio or video
Capabilities
AniPortrait can generate highly realistic and expressive facial animations from a single portrait image. The model is capable of capturing nuanced movements and expressions that closely match the provided audio or video input. This enables a range of applications, from virtual avatars to enhancing video calls and presentations.
What can I use it for?
The AniPortrait model could be useful for creating virtual assistants, video conferencing tools, or multimedia presentations where you want to animate a static portrait. It could also be used to breathe life into profile pictures or for entertainment purposes, such as short animated videos. As with any AI-generated content, it's important to be transparent about the use of such tools.
Things to try
Experiment with different types of portrait images and audio/video inputs to see the range of animations AniPortrait can produce. You could also try combining it with other models, such as GFPGAN for face restoration or Real-ESRGAN for image upscaling, to further enhance the quality of the animated output.
This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!
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