LivePortrait vs TryMotion
LivePortrait
liveportrait.github.ioTryMotion
trymotion.aiSide by side
| Figure | LivePortrait | TryMotion |
|---|---|---|
| Price from | — | — |
| Free plan | — | — |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | — |
| Windows | Yes | — |
| macOS | Yes | — |
| Linux | Yes | — |
| iOS | — | Yes |
| Self-hosted | Yes | — |
| Plans published | 0 | 0 |
| Spec score · AI Photo Animation Tools | 7.7 (#11) | 6.5 (#24) |
| integrations | Community resources include FaceFusion, ComfyUI nodes, a Stable Diffusion WebUI extension, Replicate, FAL, Poe, and Hugging Face Spaces. | The Privacy Policy names Auth0 for authentication, RevenueCat for in-app purchase management, Apple App Store for payments, and Replicate/Kling AI for generation. |
| Privacy | The repository says generated motion template files can speed inference and protect privacy. | The privacy policy says uploaded images and videos are temporarily processed and automatically deleted from processing servers after generation, while generated videos are stored on the user's device. |
| Purpose | LivePortrait animates a portrait from a still image using facial expressions and head pose from a driving video, audio, text, or generated motion. | TryMotion uses AI motion transfer to turn still images into animated videos. |
| Security | The maintainers report updating the Transformers and Gradio library versions in October 2024 to avoid security vulnerabilities. | The privacy policy lists TLS/SSL encryption in transit, encryption of sensitive data at rest, Auth0 authentication with optional multi-factor authentication, and regular security assessments. |
| Support | The maintainers invite bug reports and suggestions through repository issues and pull requests and provide a contact email for project inquiries. | TryMotion offers email support and says it typically responds within a few business days. |
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.