# LatentSync: Taming Audio-Conditioned Latent Diffusion Models for Lip Sync with SyncNet Supervision

arXiv: https://arxiv.org/abs/2412.09262 · HTML: https://mlsanity.com/paper/2412.09262/

## Key facts

- Cited by 56 papers in the map (data through 14 Oct 2026).
- Placed in Audio, speech and music, one of 14 directions in Diffusion models.
- Builds on 41 of its 53 references that are in the map.
- First posted on arXiv 12 Dec 2024.

## Placed in

- Diffusion models / [Audio, speech and music](https://mlsanity.com/diffusion/audio-speech-and-music/)

## Builds on (most cited first, 30 of 41)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [Denoising Diffusion Probabilistic Models](https://mlsanity.com/paper/2006.11239/) (2020)
- [U-Net: Convolutional Networks for Biomedical Image Segmentation](https://mlsanity.com/paper/1505.04597/) (2015)
- [High-Resolution Image Synthesis with Latent Diffusion Models](https://mlsanity.com/paper/2112.10752/) (2021)
- [Very Deep Convolutional Networks for Large-Scale Image Recognition](https://mlsanity.com/paper/1409.1556/) (2014)
- [The Unreasonable Effectiveness of Deep Features as a Perceptual Metric](https://mlsanity.com/paper/1801.03924/) (2018)
- [Denoising Diffusion Implicit Models](https://mlsanity.com/paper/2010.02502/) (2020)
- [Robust Speech Recognition via Large-Scale Weak Supervision](https://mlsanity.com/paper/2212.04356/) (2022)
- [Analyzing and Improving the Image Quality of StyleGAN](https://mlsanity.com/paper/1912.04958/) (2019)
- [Taming Transformers for High-Resolution Image Synthesis](https://mlsanity.com/paper/2012.09841/) (2020)
- [Improved Techniques for Training GANs](https://mlsanity.com/paper/1606.03498/) (2016)
- [Shortcut Learning in Deep Neural Networks](https://mlsanity.com/paper/2004.07780/) (2020)
- [Align your Latents: High-Resolution Video Synthesis with Latent Diffusion Models](https://mlsanity.com/paper/2304.08818/) (2023)
- [AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning](https://mlsanity.com/paper/2307.04725/) (2023)
- [Towards Accurate Generative Models of Video: A New Metric & Challenges](https://mlsanity.com/paper/1812.01717/) (2018)
- [VoxCeleb2: Deep Speaker Recognition](https://mlsanity.com/paper/1806.05622/) (2018)
- [A Lip Sync Expert Is All You Need for Speech to Lip Generation In The Wild](https://mlsanity.com/paper/2008.10010/) (2020)
- [MediaPipe: A Framework for Building Perception Pipelines](https://mlsanity.com/paper/1906.08172/) (2019)
- [VideoMAE V2: Scaling Video Masked Autoencoders with Dual Masking](https://mlsanity.com/paper/2303.16727/) (2023)
- [How far are we from solving the 2D & 3D Face Alignment problem? (and a dataset of 230,000 3D facial landmarks)](https://mlsanity.com/paper/1703.07332/) (2017)
- [Scaling up GANs for Text-to-Image Synthesis](https://mlsanity.com/paper/2303.05511/) (2023)
- [Diffusion Autoencoders: Toward a Meaningful and Decodable Representation](https://mlsanity.com/paper/2111.15640/) (2021)
- [EMO: Emote Portrait Alive -- Generating Expressive Portrait Videos with Audio2Video Diffusion Model under Weak Conditions](https://mlsanity.com/paper/2402.17485/) (2024)
- [StyleGAN-T: Unlocking the Power of GANs for Fast Large-Scale Text-to-Image Synthesis](https://mlsanity.com/paper/2301.09515/) (2023)
- [Hallo: Hierarchical Audio-Driven Visual Synthesis for Portrait Image Animation](https://mlsanity.com/paper/2406.08801/) (2024)
- [VEEGAN: Reducing Mode Collapse in GANs using Implicit Variational Learning](https://mlsanity.com/paper/1705.07761/) (2017)
- [EchoMimic: Lifelike Audio-Driven Portrait Animations through Editable Landmark Conditions](https://mlsanity.com/paper/2407.08136/) (2024)
- [GeneFace: Generalized and High-Fidelity Audio-Driven 3D Talking Face Synthesis](https://mlsanity.com/paper/2301.13430/) (2023)
- [Mode Regularized Generative Adversarial Networks](https://mlsanity.com/paper/1612.02136/) (2016)

## Built on by (most cited first, 30 of 56)

- [Cosmos 3: Omnimodal World Models for Physical AI](https://mlsanity.com/paper/2606.02800/) (2026)
- [HunyuanCustom: A Multimodal-Driven Architecture for Customized Video Generation](https://mlsanity.com/paper/2505.04512/) (2025)
- [HuMo: Human-Centric Video Generation via Collaborative Multi-Modal Conditioning](https://mlsanity.com/paper/2509.08519/) (2025)
- [VABench: A Comprehensive Benchmark for Audio-Video Generation](https://mlsanity.com/paper/2512.09299/) (2025)
- [T2AV-Compass: Towards Unified Evaluation for Text-to-Audio-Video Generation](https://mlsanity.com/paper/2512.21094/) (2025)
- [AnyTalker: Scaling Multi-Person Talking Video Generation with Interactivity Refinement](https://mlsanity.com/paper/2511.23475/) (2025)
- [Hallo-Live: Real-Time Streaming Joint Audio-Video Avatar Generation with Asynchronous Dual-Stream and Human-Centric Preference Distillation](https://mlsanity.com/paper/2604.23632/) (2026)
- [MSAVBench: Towards Comprehensive and Reliable Evaluation of Multi-Shot Audio-Video Generation](https://mlsanity.com/paper/2605.20183/) (2026)
- [AV-Deepfake1M++: A Large-Scale Audio-Visual Deepfake Benchmark with Real-World Perturbations](https://mlsanity.com/paper/2507.20579/) (2025)
- [Playmate2: Training-Free Multi-Character Audio-Driven Animation via Diffusion Transformer with Reward Feedback](https://mlsanity.com/paper/2510.12089/) (2025)
- [OmniShow: Unifying Multimodal Conditions for Human-Object Interaction Video Generation](https://mlsanity.com/paper/2604.11804/) (2026)
- [SceneDecorator: Towards Scene-Oriented Story Generation with Scene Planning and Scene Consistency](https://mlsanity.com/paper/2510.22994/) (2025)
- [PC-Talk: Precise Facial Animation Control for Audio-Driven Talking Face Generation](https://mlsanity.com/paper/2503.14295/) (2025)
- [Tell me Habibi, is it Real or Fake?](https://mlsanity.com/paper/2505.22581/) (2025)
- [MultiRef-Compass: Towards Comprehensive Evaluation of Multi-Reference-to-Audio-Video Generation](https://mlsanity.com/paper/2607.14189/) (2026)
- [DyStream: Streaming Dyadic Talking Heads Generation via Flow Matching-based Autoregressive Model](https://mlsanity.com/paper/2512.24408/) (2025)
- [AVBench: Human-Aligned and Automated Evaluation Benchmark for Audio-Video Generative Models](https://mlsanity.com/paper/2605.24652/) (2026)
- [EvalTalker: Learning to Evaluate Real-Portrait-Driven Multi-Subject Talking Humans](https://mlsanity.com/paper/2512.01340/) (2025)
- [DiTalker: A Unified DiT-based Framework for High-Quality and Speaking Styles Controllable Portrait Animation](https://mlsanity.com/paper/2508.06511/) (2025)
- [Soul: Breathe Life into Digital Human for High-fidelity Long-term Multimodal Animation](https://mlsanity.com/paper/2512.13495/) (2025)
- [From Inpainting to Editing: Unlocking Robust Mask-Free Visual Dubbing via Generative Bootstrapping](https://mlsanity.com/paper/2512.25066/) (2025)
- [TryOnCrafter: Unleashing Camera Trajectories for Realistic Video Virtual Try-on via a Renderable 4D Try-on Proxy](https://mlsanity.com/paper/2606.26092/) (2026)
- [EditYourself: Audio-Driven Generation and Manipulation of Talking Head Videos with Diffusion Transformers](https://mlsanity.com/paper/2601.22127/) (2026)
- [SyncBreaker:Stage-Aware Multimodal Adversarial Attacks on Audio-Driven Talking Head Generation](https://mlsanity.com/paper/2604.08405/) (2026)
- [CogPortrait: Fine-Grained Eye-Region Control in Portrait Animation via Hierarchical Agent Planning](https://mlsanity.com/paper/2605.28056/) (2026)
- [JAVEDIT: Joint Audio-Visual Instruction-Guided Video Editing with Agentic Data Curation](https://mlsanity.com/paper/2606.03168/) (2026)
- [Lip Forcing: Few-Step Autoregressive Diffusion for Real-time Lip Synchronization](https://mlsanity.com/paper/2606.11180/) (2026)
- [FauForensics: Boosting Audio-Visual Deepfake Detection with Facial Action Units](https://mlsanity.com/paper/2505.08294/) (2025)
- [SyncLipMAE: Contrastive Masked Pretraining for Audio-Visual Talking-Face Representation](https://mlsanity.com/paper/2510.10069/) (2025)
- [VividAnimator: An End-to-End Audio and Pose-driven Half-Body Human Animation Framework](https://mlsanity.com/paper/2510.10269/) (2025)

## Abstract (arXiv)

End-to-end audio-conditioned latent diffusion models (LDMs) have been widely adopted for audio-driven portrait animation, demonstrating their effectiveness in generating lifelike and high-resolution talking videos. However, direct application of audio-conditioned LDMs to lip-synchronization (lip-sync) tasks results in suboptimal lip-sync accuracy. Through an in-depth analysis, we identified the underlying cause as the "shortcut learning problem", wherein the model predominantly learns visual-visual shortcuts while neglecting the critical audio-visual correlations. To address this issue, we explored different approaches for integrating SyncNet supervision into audio-conditioned LDMs to explicitly enforce the learning of audio-visual correlations. Since the performance of SyncNet directly influences the lip-sync accuracy of the supervised model, the training of a well-converged SyncNet becomes crucial. We conducted the first comprehensive empirical studies to identify key factors affecting SyncNet convergence. Based on our analysis, we introduce StableSyncNet, with an architecture designed for stable convergence. Our StableSyncNet achieved a significant improvement in accuracy, increasing from 91% to 94% on the HDTF test set. Additionally, we introduce a novel Temporal Representation Alignment (TREPA) mechanism to enhance temporal consistency in the generated videos. Experimental results show that our method surpasses state-of-the-art lip-sync approaches across various evaluation metrics on the HDTF and VoxCeleb2 datasets.