# LSF-Animation: Label-Free Speech-Driven Facial Animation via Implicit Feature Representation

arXiv: https://arxiv.org/abs/2510.21864 · HTML: https://mlsanity.com/paper/2510.21864/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 37 of its 51 references that are in the map.
- First posted on arXiv 23 Oct 2025.

## Builds on (most cited first, 30 of 37)

- [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)
- [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)
- [MeshTalk: 3D Face Animation from Speech using Cross-Modality Disentanglement](https://mlsanity.com/paper/2104.08223/) (2021)
- [CodeTalker: Speech-Driven 3D Facial Animation with Discrete Motion Prior](https://mlsanity.com/paper/2301.02379/) (2023)
- [Audio-Driven Emotional Video Portraits](https://mlsanity.com/paper/2104.07452/) (2021)
- [Towards Metrical Reconstruction of Human Faces](https://mlsanity.com/paper/2204.06607/) (2022)
- [EAMM: One-Shot Emotional Talking Face via Audio-Based Emotion-Aware Motion Model](https://mlsanity.com/paper/2205.15278/) (2022)
- [GANFIT: Generative Adversarial Network Fitting for High Fidelity 3D Face Reconstruction](https://mlsanity.com/paper/1902.05978/) (2019)
- [Diffused Heads: Diffusion Models Beat GANs on Talking-Face Generation](https://mlsanity.com/paper/2301.03396/) (2023)
- [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)
- [Emotional Speech-Driven Animation with Content-Emotion Disentanglement](https://mlsanity.com/paper/2306.08990/) (2023)
- [Multiface: A Dataset for Neural Face Rendering](https://mlsanity.com/paper/2207.11243/) (2022)
- [From Audio to Photoreal Embodiment: Synthesizing Humans in Conversations](https://mlsanity.com/paper/2401.01885/) (2024)
- [DiffPoseTalk: Speech-Driven Stylistic 3D Facial Animation and Head Pose Generation via Diffusion Models](https://mlsanity.com/paper/2310.00434/) (2023)
- [FaceDiffuser: Speech-Driven 3D Facial Animation Synthesis Using Diffusion](https://mlsanity.com/paper/2309.11306/) (2023)
- [Imitator: Personalized Speech-driven 3D Facial Animation](https://mlsanity.com/paper/2301.00023/) (2022)
- [VisemeNet: Audio-Driven Animator-Centric Speech Animation](https://mlsanity.com/paper/1805.09488/) (2018)
- [FaceTalk: Audio-Driven Motion Diffusion for Neural Parametric Head Models](https://mlsanity.com/paper/2312.08459/) (2023)
- [Media2Face: Co-speech Facial Animation Generation With Multi-Modality Guidance](https://mlsanity.com/paper/2401.15687/) (2024)
- [MonoNPHM: Dynamic Head Reconstruction from Monocular Videos](https://mlsanity.com/paper/2312.06740/) (2023)
- [Supervision by Registration and Triangulation for Landmark Detection](https://mlsanity.com/paper/2101.09866/) (2021)
- [ExpNet: Landmark-Free, Deep, 3D Facial Expressions](https://mlsanity.com/paper/1802.00542/) (2018)
- [FaceXHuBERT: Text-less Speech-driven E(X)pressive 3D Facial Animation Synthesis Using Self-Supervised Speech Representation Learning](https://mlsanity.com/paper/2303.05416/) (2023)
- [Unveiling the Power of Audio-Visual Early Fusion Transformers with Dense Interactions through Masked Modeling](https://mlsanity.com/paper/2312.01017/) (2023)
- [FacePoseNet: Making a Case for Landmark-Free Face Alignment](https://mlsanity.com/paper/1708.07517/) (2017)
- [Sparse to Dense Dynamic 3D Facial Expression Generation](https://mlsanity.com/paper/2105.07463/) (2021)

## Built on by (most cited first, 3 of 3)

- [OMEGA-Avatar: One-shot Modeling of 360deg Gaussian Avatars](https://mlsanity.com/paper/2602.11693/) (2026)
- [SubtleTalk: Generating Controllable Weakly-correlated Facial Dynamics for 3D Talking Heads via Residual Flow Matching](https://mlsanity.com/paper/2608.06408/) (2026)
- [Seeing Speech: Learning Visible Articulatory Dynamics for Speech-Driven 3D Facial Animation](https://mlsanity.com/paper/2609.30517/) (2026)

## Abstract (arXiv)

Speech-driven 3D facial animation has attracted increasing interest since its potential to generate expressive and temporally synchronized digital humans. While recent works have begun to explore emotion-aware animation, they still depend on explicit one-hot encodings to represent identity and emotion with given emotion and identity labels, which limits their ability to generalize to unseen speakers. Moreover, the emotional cues inherently present in speech are often neglected, limiting the naturalness and adaptability of generated animations. In this work, we propose LSF-Animation, a novel framework that eliminates the reliance on explicit emotion and identity feature representations. Specifically, LSF-Animation implicitly extracts emotion information from speech and captures the identity features from a neutral facial mesh, enabling improved generalization to unseen speakers and emotional states without requiring manual labels. Furthermore, we introduce a Hierarchical Interaction Fusion Block (HIFB), which employs a fusion token to integrate dual transformer features and more effectively integrate emotional, motion-related and identity-related cues. Extensive experiments conducted on the 3DMEAD dataset demonstrate that our method surpasses recent state-of-the-art approaches in terms of emotional expressiveness, identity generalization, and animation realism. The source code will be released at: https://github.com/Dogter521/LSF-Animation.