# Media2Face: Co-speech Facial Animation Generation With Multi-Modality Guidance

arXiv: https://arxiv.org/abs/2401.15687 · HTML: https://mlsanity.com/paper/2401.15687/

## Key facts

- Cited by 39 papers in the map (data through 14 Oct 2026).
- Builds on 60 of its 91 references that are in the map.
- First posted on arXiv 28 Jan 2024.

## Builds on (most cited first, 30 of 60)

- [Learning Transferable Visual Models From Natural Language Supervision](https://mlsanity.com/paper/2103.00020/) (2021)
- [Denoising Diffusion Probabilistic Models](https://mlsanity.com/paper/2006.11239/) (2020)
- [High-Resolution Image Synthesis with Latent Diffusion Models](https://mlsanity.com/paper/2112.10752/) (2021)
- [Deep Unsupervised Learning using Nonequilibrium Thermodynamics](https://mlsanity.com/paper/1503.03585/) (2015)
- [Classifier-Free Diffusion Guidance](https://mlsanity.com/paper/2207.12598/) (2022)
- [Neural Discrete Representation Learning](https://mlsanity.com/paper/1711.00937/) (2017)
- [wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations](https://mlsanity.com/paper/2006.11477/) (2020)
- [An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion](https://mlsanity.com/paper/2208.01618/) (2022)
- [Diffusion Models: A Comprehensive Survey of Methods and Applications](https://mlsanity.com/paper/2209.00796/) (2022)
- [Human Motion Diffusion Model](https://mlsanity.com/paper/2209.14916/) (2022)
- [Learning an Animatable Detailed 3D Face Model from In-The-Wild Images](https://mlsanity.com/paper/2012.04012/) (2020)
- [SadTalker: Learning Realistic 3D Motion Coefficients for Stylized Audio-Driven Single Image Talking Face Animation](https://mlsanity.com/paper/2211.12194/) (2022)
- [Human Motion Diffusion as a Generative Prior](https://mlsanity.com/paper/2303.01418/) (2023)
- [3D Morphable Face Models -- Past, Present and Future](https://mlsanity.com/paper/1909.01815/) (2019)
- [Capture, Learning, and Synthesis of 3D Speaking Styles](https://mlsanity.com/paper/1905.03079/) (2019)
- [EMOCA: Emotion Driven Monocular Face Capture and Animation](https://mlsanity.com/paper/2204.11312/) (2022)
- [Neural Voice Puppetry: Audio-driven Facial Reenactment](https://mlsanity.com/paper/1912.05566/) (2019)
- [FaceFormer: Speech-Driven 3D Facial Animation with Transformers](https://mlsanity.com/paper/2112.05329/) (2021)
- [MeshTalk: 3D Face Animation from Speech using Cross-Modality Disentanglement](https://mlsanity.com/paper/2104.08223/) (2021)
- [Listen, Denoise, Action! Audio-Driven Motion Synthesis with Diffusion Models](https://mlsanity.com/paper/2211.09707/) (2022)
- [CodeTalker: Speech-Driven 3D Facial Animation with Discrete Motion Prior](https://mlsanity.com/paper/2301.02379/) (2023)
- [Generating Holistic 3D Human Motion from Speech](https://mlsanity.com/paper/2212.04420/) (2022)
- [BEAT: A Large-Scale Semantic and Emotional Multi-Modal Dataset for Conversational Gestures Synthesis](https://mlsanity.com/paper/2203.05297/) (2022)
- [GestureDiffuCLIP: Gesture Diffusion Model with CLIP Latents](https://mlsanity.com/paper/2303.14613/) (2023)
- [Nonlinear 3D Face Morphable Model](https://mlsanity.com/paper/1804.03786/) (2018)
- [EmoTalk: Speech-Driven Emotional Disentanglement for 3D Face Animation](https://mlsanity.com/paper/2303.11089/) (2023)
- [Learning to Listen: Modeling Non-Deterministic Dyadic Facial Motion](https://mlsanity.com/paper/2204.08451/) (2022)
- [i3DMM: Deep Implicit 3D Morphable Model of Human Heads](https://mlsanity.com/paper/2011.14143/) (2020)
- [Emotional Speech-Driven Animation with Content-Emotion Disentanglement](https://mlsanity.com/paper/2306.08990/) (2023)
- [Learning Formation of Physically-Based Face Attributes](https://mlsanity.com/paper/2004.03458/) (2020)

## Built on by (most cited first, 30 of 39)

- [UniTalker: Scaling up Audio-Driven 3D Facial Animation through A Unified Model](https://mlsanity.com/paper/2408.00762/) (2024)
- [Human Motion Video Generation: A Survey](https://mlsanity.com/paper/2509.03883/) (2025)
- [DiffSpeaker: Speech-Driven 3D Facial Animation with Diffusion Transformer](https://mlsanity.com/paper/2402.05712/) (2024)
- [Learn2Talk: 3D Talking Face Learns from 2D Talking Face](https://mlsanity.com/paper/2404.12888/) (2024)
- [InstructAvatar: Text-Guided Emotion and Motion Control for Avatar Generation](https://mlsanity.com/paper/2405.15758/) (2024)
- [MMHead: Towards Fine-grained Multi-modal 3D Facial Animation](https://mlsanity.com/paper/2410.07757/) (2024)
- [Beyond Talking -- Generating Holistic 3D Human Dyadic Motion for Communication](https://mlsanity.com/paper/2403.19467/) (2024)
- [FixTalk: Taming Identity Leakage for High-Quality Talking Head Generation in Extreme Cases](https://mlsanity.com/paper/2507.01390/) (2025)
- [ProbTalk3D: Non-Deterministic Emotion Controllable Speech-Driven 3D Facial Animation Synthesis Using VQ-VAE](https://mlsanity.com/paper/2409.07966/) (2024)
- [Cafe-Talk: Generating 3D Talking Face Animation with Multimodal Coarse- and Fine-grained Control](https://mlsanity.com/paper/2503.14517/) (2025)
- [DICE: End-to-end Deformation Capture of Hand-Face Interactions from a Single Image](https://mlsanity.com/paper/2406.17988/) (2024)
- [MemoryTalker: Personalized Speech-Driven 3D Facial Animation via Audio-Guided Stylization](https://mlsanity.com/paper/2507.20562/) (2025)
- [Wav2Sem: Plug-and-Play Audio Semantic Decoupling for 3D Speech-Driven Facial Animation](https://mlsanity.com/paper/2505.23290/) (2025)
- [Model See Model Do: Speech-Driven Facial Animation with Style Control](https://mlsanity.com/paper/2505.01319/) (2025)
- [Audio-Driven Universal Gaussian Head Avatars](https://mlsanity.com/paper/2509.18924/) (2025)
- [Advancing Talking Head Generation: A Comprehensive Survey of Multi-Modal Methodologies, Datasets, Evaluation Metrics, and Loss Functions](https://mlsanity.com/paper/2507.02900/) (2025)
- [MEDTalk: Multimodal Controlled 3D Facial Animation with Dynamic Emotions by Disentangled Embedding](https://mlsanity.com/paper/2507.06071/) (2025)
- [Towards High-fidelity 3D Talking Avatar with Personalized Dynamic Texture](https://mlsanity.com/paper/2503.00495/) (2025)
- [Supervising 3D Talking Head Avatars with Analysis-by-Audio-Synthesis](https://mlsanity.com/paper/2504.13386/) (2025)
- [Audio Driven Real-Time Facial Animation for Social Telepresence](https://mlsanity.com/paper/2510.01176/) (2025)
- [SEREP: Semantic Facial Expression Representation for Robust In-the-Wild Capture and Retargeting](https://mlsanity.com/paper/2412.14371/) (2024)
- [Exploring Timeline Control for Facial Motion Generation](https://mlsanity.com/paper/2505.20861/) (2025)
- [3DiFACE: Synthesizing and Editing Holistic 3D Facial Animation](https://mlsanity.com/paper/2509.26233/) (2025)
- [SMGDiff: Soccer Motion Generation using diffusion probabilistic models](https://mlsanity.com/paper/2411.16216/) (2024)
- [LSF-Animation: Label-Free Speech-Driven Facial Animation via Implicit Feature Representation](https://mlsanity.com/paper/2510.21864/) (2025)
- [VividListener: Expressive and Controllable Listener Dynamics Modeling for Multi-Modal Responsive Interaction](https://mlsanity.com/paper/2504.21718/) (2025)
- [Tiny is not small enough: High-quality, low-resource facial animation models through hybrid knowledge distillation](https://mlsanity.com/paper/2507.18352/) (2025)
- [InterAct: A Large-Scale Dataset of Dynamic, Expressive and Interactive Activities between Two People in Daily Scenarios](https://mlsanity.com/paper/2509.05747/) (2025)
- [EmoDiffusion: Enhancing Emotional 3D Facial Animation with Latent Diffusion Models](https://mlsanity.com/paper/2503.11028/) (2025)
- [ExFace: Expressive Facial Control for Humanoid Robots with Diffusion Transformers and Bootstrap Training](https://mlsanity.com/paper/2504.14477/) (2025)

## Abstract (arXiv)

The synthesis of 3D facial animations from speech has garnered considerable attention. Due to the scarcity of high-quality 4D facial data and well-annotated abundant multi-modality labels, previous methods often suffer from limited realism and a lack of lexible conditioning. We address this challenge through a trilogy. We first introduce Generalized Neural Parametric Facial Asset (GNPFA), an efficient variational auto-encoder mapping facial geometry and images to a highly generalized expression latent space, decoupling expressions and identities. Then, we utilize GNPFA to extract high-quality expressions and accurate head poses from a large array of videos. This presents the M2F-D dataset, a large, diverse, and scan-level co-speech 3D facial animation dataset with well-annotated emotional and style labels. Finally, we propose Media2Face, a diffusion model in GNPFA latent space for co-speech facial animation generation, accepting rich multi-modality guidances from audio, text, and image. Extensive experiments demonstrate that our model not only achieves high fidelity in facial animation synthesis but also broadens the scope of expressiveness and style adaptability in 3D facial animation.