# Lip Movements Generation at a Glance

arXiv: https://arxiv.org/abs/1803.10404 · HTML: https://mlsanity.com/paper/1803.10404/

## Key facts

- Cited by 155 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 Mar 2018.

## Built on by (most cited first, 30 of 155)

- [Pose-Controllable Talking Face Generation by Implicitly Modularized Audio-Visual Representation](https://mlsanity.com/paper/2104.11116/) (2021)
- [Learning Audio-Visual Speech Representation by Masked Multimodal Cluster Prediction](https://mlsanity.com/paper/2201.02184/) (2022)
- [FaceFormer: Speech-Driven 3D Facial Animation with Transformers](https://mlsanity.com/paper/2112.05329/) (2021)
- [VASA-1: Lifelike Audio-Driven Talking Faces Generated in Real Time](https://mlsanity.com/paper/2404.10667/) (2024)
- [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)
- [GeneFace: Generalized and High-Fidelity Audio-Driven 3D Talking Face Synthesis](https://mlsanity.com/paper/2301.13430/) (2023)
- [Pros and Cons of GAN Evaluation Measures: New Developments](https://mlsanity.com/paper/2103.09396/) (2021)
- [Semantic-Aware Implicit Neural Audio-Driven Video Portrait Generation](https://mlsanity.com/paper/2201.07786/) (2022)
- [Progressive Disentangled Representation Learning for Fine-Grained Controllable Talking Head Synthesis](https://mlsanity.com/paper/2211.14506/) (2022)
- [StyleTalk: One-shot Talking Head Generation with Controllable Speaking Styles](https://mlsanity.com/paper/2301.01081/) (2023)
- [FACIAL: Synthesizing Dynamic Talking Face with Implicit Attribute Learning](https://mlsanity.com/paper/2108.07938/) (2021)
- [StyleSync: High-Fidelity Generalized and Personalized Lip Sync in Style-based Generator](https://mlsanity.com/paper/2305.05445/) (2023)
- [One-shot Talking Face Generation from Single-speaker Audio-Visual Correlation Learning](https://mlsanity.com/paper/2112.02749/) (2021)
- [SyncTalk: The Devil is in the Synchronization for Talking Head Synthesis](https://mlsanity.com/paper/2311.17590/) (2023)
- [Real-time Neural Radiance Talking Portrait Synthesis via Audio-spatial Decomposition](https://mlsanity.com/paper/2211.12368/) (2022)
- [DFA-NeRF: Personalized Talking Head Generation via Disentangled Face Attributes Neural Rendering](https://mlsanity.com/paper/2201.00791/) (2022)
- [EDTalk: Efficient Disentanglement for Emotional Talking Head Synthesis](https://mlsanity.com/paper/2404.01647/) (2024)
- [DINet: Deformation Inpainting Network for Realistic Face Visually Dubbing on High Resolution Video](https://mlsanity.com/paper/2303.03988/) (2023)
- [Efficient Region-Aware Neural Radiance Fields for High-Fidelity Talking Portrait Synthesis](https://mlsanity.com/paper/2307.09323/) (2023)
- [Sonic: Shifting Focus to Global Audio Perception in Portrait Animation](https://mlsanity.com/paper/2411.16331/) (2024)
- [LipSync3D: Data-Efficient Learning of Personalized 3D Talking Faces from Video using Pose and Lighting Normalization](https://mlsanity.com/paper/2106.04185/) (2021)
- [Deepfake Generation and Detection: A Benchmark and Survey](https://mlsanity.com/paper/2403.17881/) (2024)
- [SyncTalkFace: Talking Face Generation with Precise Lip-Syncing via Audio-Lip Memory](https://mlsanity.com/paper/2211.00924/) (2022)
- [TalkingGaussian: Structure-Persistent 3D Talking Head Synthesis via Gaussian Splatting](https://mlsanity.com/paper/2404.15264/) (2024)
- [Cyclic Co-Learning of Sounding Object Visual Grounding and Sound Separation](https://mlsanity.com/paper/2104.02026/) (2021)
- [Speech Drives Templates: Co-Speech Gesture Synthesis with Learned Templates](https://mlsanity.com/paper/2108.08020/) (2021)
- [Imitating Arbitrary Talking Style for Realistic Audio-DrivenTalking Face Synthesis](https://mlsanity.com/paper/2111.00203/) (2021)
- [Diff2Lip: Audio Conditioned Diffusion Models for Lip-Synchronization](https://mlsanity.com/paper/2308.09716/) (2023)
- [DAE-Talker: High Fidelity Speech-Driven Talking Face Generation with Diffusion Autoencoder](https://mlsanity.com/paper/2303.17550/) (2023)

## Abstract (arXiv)

Cross-modality generation is an emerging topic that aims to synthesize data in one modality based on information in a different modality. In this paper, we consider a task of such: given an arbitrary audio speech and one lip image of arbitrary target identity, generate synthesized lip movements of the target identity saying the speech. To perform well in this task, it inevitably requires a model to not only consider the retention of target identity, photo-realistic of synthesized images, consistency and smoothness of lip images in a sequence, but more importantly, learn the correlations between audio speech and lip movements. To solve the collective problems, we explore the best modeling of the audio-visual correlations in building and training a lip-movement generator network. Specifically, we devise a method to fuse audio and image embeddings to generate multiple lip images at once and propose a novel correlation loss to synchronize lip changes and speech changes. Our final model utilizes a combination of four losses for a comprehensive consideration in generating lip movements; it is trained in an end-to-end fashion and is robust to lip shapes, view angles and different facial characteristics. Thoughtful experiments on three datasets ranging from lab-recorded to lips in-the-wild show that our model significantly outperforms other state-of-the-art methods extended to this task.