Talking Head Generation
40 papers with code • 7 benchmarks • 3 datasets
Talking head generation is the task of generating a talking face from a set of images of a person.
( Image credit: Few-Shot Adversarial Learning of Realistic Neural Talking Head Models )
Benchmarks
These leaderboards are used to track progress in Talking Head Generation
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VoxCeleb1
VoxCeleb2
AnimeCeleb
Latest papers
DaGAN++: Depth-Aware Generative Adversarial Network for Talking Head Video Generation
In this work, firstly, we present a novel self-supervised method for learning dense 3D facial geometry (ie, depth) from face videos, without requiring camera parameters and 3D geometry annotations in training.
Face Animation with an Attribute-Guided Diffusion Model
Face animation has achieved much progress in computer vision.
Emotionally Enhanced Talking Face Generation
sahilg06/EmoGen
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To mitigate this, we build a talking face generation framework conditioned on a categorical emotion to generate videos with appropriate expressions, making them more realistic and convincing.
DisCoHead: Audio-and-Video-Driven Talking Head Generation by Disentangled Control of Head Pose and Facial Expressions
We enhance the efficiency of DisCoHead by integrating a dense motion estimator and the encoder of a generator which are originally separate modules.
DiffTalk: Crafting Diffusion Models for Generalized Audio-Driven Portraits Animation
In this way, the proposed DiffTalk is capable of producing high-quality talking head videos in synchronization with the source audio, and more importantly, it can be naturally generalized across different identities without any further fine-tuning.
StyleTalk: One-shot Talking Head Generation with Controllable Speaking Styles
fuxivirtualhuman/styletalk
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In a nutshell, we aim to attain a speaking style from an arbitrary reference speaking video and then drive the one-shot portrait to speak with the reference speaking style and another piece of audio.
MetaPortrait: Identity-Preserving Talking Head Generation with Fast Personalized Adaptation
Meta-Portrait/MetaPortrait
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CVPR 2023
In this work, we propose an ID-preserving talking head generation framework, which advances previous methods in two aspects.
SadTalker: Learning Realistic 3D Motion Coefficients for Stylized Audio-Driven Single Image Talking Face Animation
winfredy/sadtalker
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CVPR 2023
We present SadTalker, which generates 3D motion coefficients (head pose, expression) of the 3DMM from audio and implicitly modulates a novel 3D-aware face render for talking head generation.
Autoregressive GAN for Semantic Unconditional Head Motion Generation
louisbearing/unconditionalheadmotion
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In this work, we address the task of unconditional head motion generation to animate still human faces in a low-dimensional semantic space from a single reference pose.
Compressing Video Calls using Synthetic Talking Heads
berlin0610/awesome-generative-face-video-coding
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We use a state-of-the-art face reenactment network to detect key points in the non-pivot frames and transmit them to the receiver.
