# Identity-Preserving Talking Face Generation with Landmark and Appearance Priors

arXiv: https://arxiv.org/abs/2305.08293 · HTML: https://mlsanity.com/paper/2305.08293/

## Key facts

- Cited by 98 papers in the map (data through 14 Oct 2026).
- Builds on 36 of its 56 references that are in the map.
- First posted on arXiv 15 May 2023.

## Builds on (most cited first, 30 of 36)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014)
- [PyTorch: An Imperative Style, High-Performance Deep Learning Library](https://mlsanity.com/paper/1912.01703/) (2019)
- [The Unreasonable Effectiveness of Deep Features as a Perceptual Metric](https://mlsanity.com/paper/1801.03924/) (2018)
- [Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift](https://mlsanity.com/paper/1502.03167/) (2015)
- [Perceptual Losses for Real-Time Style Transfer and Super-Resolution](https://mlsanity.com/paper/1603.08155/) (2016)
- [Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization](https://mlsanity.com/paper/1703.06868/) (2017)
- [Semantic Image Synthesis with Spatially-Adaptive Normalization](https://mlsanity.com/paper/1903.07291/) (2019)
- [Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network](https://mlsanity.com/paper/1609.05158/) (2016)
- [High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs](https://mlsanity.com/paper/1711.11585/) (2017)
- [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)
- [One-Shot Free-View Neural Talking-Head Synthesis for Video Conferencing](https://mlsanity.com/paper/2011.15126/) (2020)
- [AD-NeRF: Audio Driven Neural Radiance Fields for Talking Head Synthesis](https://mlsanity.com/paper/2103.11078/) (2021)
- [Deep Audio-Visual Speech Recognition](https://mlsanity.com/paper/1809.02108/) (2018)
- [MakeItTalk: Speaker-Aware Talking-Head Animation](https://mlsanity.com/paper/2004.12992/) (2020)
- [LRS3-TED: a large-scale dataset for visual speech recognition](https://mlsanity.com/paper/1809.00496/) (2018)
- [Pose-Controllable Talking Face Generation by Implicitly Modularized Audio-Visual Representation](https://mlsanity.com/paper/2104.11116/) (2021)
- [Hierarchical Cross-Modal Talking Face Generationwith Dynamic Pixel-Wise Loss](https://mlsanity.com/paper/1905.03820/) (2019)
- [Neural Voice Puppetry: Audio-driven Facial Reenactment](https://mlsanity.com/paper/1912.05566/) (2019)
- [PIRenderer: Controllable Portrait Image Generation via Semantic Neural Rendering](https://mlsanity.com/paper/2109.08379/) (2021)
- [Audio-Driven Emotional Video Portraits](https://mlsanity.com/paper/2104.07452/) (2021)
- [EAMM: One-Shot Emotional Talking Face via Audio-Based Emotion-Aware Motion Model](https://mlsanity.com/paper/2205.15278/) (2022)
- [Semantic-Aware Implicit Neural Audio-Driven Video Portrait Generation](https://mlsanity.com/paper/2201.07786/) (2022)
- [Talking-head Generation with Rhythmic Head Motion](https://mlsanity.com/paper/2007.08547/) (2020)
- [You said that?](https://mlsanity.com/paper/1705.02966/) (2017)
- [Learning Dynamic Facial Radiance Fields for Few-Shot Talking Head Synthesis](https://mlsanity.com/paper/2207.11770/) (2022)
- [Towards Automatic Face-to-Face Translation](https://mlsanity.com/paper/2003.00418/) (2020)
- [FACIAL: Synthesizing Dynamic Talking Face with Implicit Attribute Learning](https://mlsanity.com/paper/2108.07938/) (2021)
- [One-shot Talking Face Generation from Single-speaker Audio-Visual Correlation Learning](https://mlsanity.com/paper/2112.02749/) (2021)

## Built on by (most cited first, 30 of 98)

- [SyncTalk: The Devil is in the Synchronization for Talking Head Synthesis](https://mlsanity.com/paper/2311.17590/) (2023)
- [EDTalk: Efficient Disentanglement for Emotional Talking Head Synthesis](https://mlsanity.com/paper/2404.01647/) (2024)
- [Deepfake Generation and Detection: A Benchmark and Survey](https://mlsanity.com/paper/2403.17881/) (2024)
- [AniTalker: Animate Vivid and Diverse Talking Faces through Identity-Decoupled Facial Motion Encoding](https://mlsanity.com/paper/2405.03121/) (2024)
- [TalkingGaussian: Structure-Persistent 3D Talking Head Synthesis via Gaussian Splatting](https://mlsanity.com/paper/2404.15264/) (2024)
- [VividTalk: One-Shot Audio-Driven Talking Head Generation Based on 3D Hybrid Prior](https://mlsanity.com/paper/2312.01841/) (2023)
- [GAIA: Zero-shot Talking Avatar Generation](https://mlsanity.com/paper/2311.15230/) (2023)
- [FlowVQTalker: High-Quality Emotional Talking Face Generation through Normalizing Flow and Quantization](https://mlsanity.com/paper/2403.06375/) (2024)
- [MoCha: Towards Movie-Grade Talking Character Synthesis](https://mlsanity.com/paper/2503.23307/) (2025)
- [MuseTalk: Real-Time High-Fidelity Video Dubbing via Spatio-Temporal Sampling](https://mlsanity.com/paper/2410.10122/) (2024)
- [OmniSync: Towards Universal Lip Synchronization via Diffusion Transformers](https://mlsanity.com/paper/2505.21448/) (2025)
- [FT2TF: First-Person Statement Text-To-Talking Face Generation](https://mlsanity.com/paper/2312.05430/) (2023)
- [DREAM-Talk: Diffusion-based Realistic Emotional Audio-driven Method for Single Image Talking Face Generation](https://mlsanity.com/paper/2312.13578/) (2023)
- [Human Motion Video Generation: A Survey](https://mlsanity.com/paper/2509.03883/) (2025)
- [ScanTalk: 3D Talking Heads from Unregistered Scans](https://mlsanity.com/paper/2403.10942/) (2024)
- [GaussianTalker: Speaker-specific Talking Head Synthesis via 3D Gaussian Splatting](https://mlsanity.com/paper/2404.14037/) (2024)
- [Celeb-DF++: A Large-scale Challenging Video DeepFake Benchmark for Generalizable Forensics](https://mlsanity.com/paper/2507.18015/) (2025)
- [FaceChain-ImagineID: Freely Crafting High-Fidelity Diverse Talking Faces from Disentangled Audio](https://mlsanity.com/paper/2403.01901/) (2024)
- [Audio-Visual Speech Representation Expert for Enhanced Talking Face Video Generation and Evaluation](https://mlsanity.com/paper/2405.04327/) (2024)
- [PersonaTalk: Bring Attention to Your Persona in Visual Dubbing](https://mlsanity.com/paper/2409.05379/) (2024)
- [RealTalk: Real-time and Realistic Audio-driven Face Generation with 3D Facial Prior-guided Identity Alignment Network](https://mlsanity.com/paper/2406.18284/) (2024)
- [FixTalk: Taming Identity Leakage for High-Quality Talking Head Generation in Extreme Cases](https://mlsanity.com/paper/2507.01390/) (2025)
- [Audio-driven Talking Face Generation with Stabilized Synchronization Loss](https://mlsanity.com/paper/2307.09368/) (2023)
- [SayAnything: Audio-Driven Lip Synchronization with Conditional Video Diffusion](https://mlsanity.com/paper/2502.11515/) (2025)
- [KeySync: A Robust Approach for Leakage-free Lip Synchronization in High Resolution](https://mlsanity.com/paper/2505.00497/) (2025)
- [FlowAct-R1: Towards Interactive Humanoid Video Generation](https://mlsanity.com/paper/2601.10103/) (2026)
- [DiffDub: Person-generic Visual Dubbing Using Inpainting Renderer with Diffusion Auto-encoder](https://mlsanity.com/paper/2311.01811/) (2023)
- [Deepfake Media Generation and Detection in the Generative AI Era: A Survey and Outlook](https://mlsanity.com/paper/2411.19537/) (2024)
- [Monocular and Generalizable Gaussian Talking Head Animation](https://mlsanity.com/paper/2504.00665/) (2025)
- [SyncTalk++: High-Fidelity and Efficient Synchronized Talking Heads Synthesis Using Gaussian Splatting](https://mlsanity.com/paper/2506.14742/) (2025)

## Abstract (arXiv)

Generating talking face videos from audio attracts lots of research interest. A few person-specific methods can generate vivid videos but require the target speaker's videos for training or fine-tuning. Existing person-generic methods have difficulty in generating realistic and lip-synced videos while preserving identity information. To tackle this problem, we propose a two-stage framework consisting of audio-to-landmark generation and landmark-to-video rendering procedures. First, we devise a novel Transformer-based landmark generator to infer lip and jaw landmarks from the audio. Prior landmark characteristics of the speaker's face are employed to make the generated landmarks coincide with the facial outline of the speaker. Then, a video rendering model is built to translate the generated landmarks into face images. During this stage, prior appearance information is extracted from the lower-half occluded target face and static reference images, which helps generate realistic and identity-preserving visual content. For effectively exploring the prior information of static reference images, we align static reference images with the target face's pose and expression based on motion fields. Moreover, auditory features are reused to guarantee that the generated face images are well synchronized with the audio. Extensive experiments demonstrate that our method can produce more realistic, lip-synced, and identity-preserving videos than existing person-generic talking face generation methods.