Face Transfer
3 papers with code • 0 benchmarks • 1 datasets
Face Transfer is a method for mapping face performances of one individual to facial animations of another one. It uses facial expressions and head poses from the video of a source actor to generate a video of a target character. Face Transfer is a special case of image-to-image translation tasks.
Benchmarks
These leaderboards are used to track progress in Face Transfer
VGGFace2 HQ
Latest papers with no code
FT-Shield: A Watermark Against Unauthorized Fine-tuning in Text-to-Image Diffusion Models
Text-to-image generative models based on latent diffusion models (LDM) have demonstrated their outstanding ability in generating high-quality and high-resolution images according to language prompt.
Causal Representation Learning for Context-Aware Face Transfer
Human face synthesis involves transferring knowledge about the identity and identity-dependent face shape (IDFS) of a human face to target face images where the context (e. g., facial expressions, head poses, and other background factors) may change dramatically.
Geometry Guided Adversarial Facial Expression Synthesis
An expression invariant face recognition experiment is also performed to further show the advantages of our proposed method.
Face Transfer with Generative Adversarial Network
Face transfer animates the facial performances of the character in the target video by a source actor.
Automatic Face Reenactment
We propose an image-based, facial reenactment system that replaces the face of an actor in an existing target video with the face of a user from a source video, while preserving the original target performance.
