LivePortrait vs VIMAGE
LivePortrait
liveportrait.github.io
VIMAGE
vimageapp.comSide by side
| Figure | LivePortrait | VIMAGE |
|---|---|---|
| Price from | — | — |
| Free plan | — | — |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | Yes |
| Windows | Yes | — |
| macOS | Yes | — |
| Linux | Yes | — |
| iOS | — | Yes |
| Android | — | Yes |
| Self-hosted | Yes | — |
| Plans published | 0 | 1 |
| Spec score · Photo Animation Software | 7.7 (#12) | 7.2 (#22) |
| integrations | Community resources include FaceFusion, ComfyUI nodes, a Stable Diffusion WebUI extension, Replicate, FAL, Poe, and Hugging Face Spaces. | VIMAGE’s stock photo library includes photos from Unsplash, which it identifies as its official stock photo partner. |
| Privacy | The repository says generated motion template files can speed inference and protect privacy. | VIMAGE’s privacy policy says uploaded images are not disclosed unless the user explicitly consents to showing them on VIMAGE or third-party services. |
| Security | The maintainers report updating the Transformers and Gradio library versions in October 2024 to avoid security vulnerabilities. | The privacy policy says VIMAGE uses technology and policies intended to protect against unauthorized access and improper use, but does not guarantee security measures cannot be defeated. |
| Support | The maintainers invite bug reports and suggestions through repository issues and pull requests and provide a contact email for project inquiries. | The app page directs technical support questions and suggestions to [email protected]. |
Plans
In their own words
LivePortrait
LivePortrait creates portrait video from a single image, using motion from video, audio, text, or generation. It also supports editing portrait video using a source video and a driving video. Stitching and eye and lip retargeting controls provide ways to adjust animation. The project supplies inference code, pretrained models, and a Gradio interface for local use, as well as a demo hosted on Hugging Face Spaces. Its PyTorch implementation is released under the MIT License, and the project reports generation speed of 12.8 ms on an RTX 4090 GPU with PyTorch. Human-mode instructions cover Linux, Windows, and Apple Silicon macOS; Intel macOS is untested. Animal models can animate cats, dogs, and pandas using human-driven motion, but animal mode is tested only on Linux and Windows with an NVIDIA GPU and is unsupported on macOS. Local setup requires git, conda, FFmpeg, Python 3.10, and downloaded pretrained weights. Commercial users must replace the included InsightFace detection models. Maintainers warn of possible deepfake misuse and visual artifacts.