# Embedded Representation Learning Network for Animating Styled Video Portrait

arXiv: https://arxiv.org/abs/2404.19038 · HTML: https://mlsanity.com/paper/2404.19038/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 32 of its 41 references that are in the map.
- First posted on arXiv 29 Apr 2024.

## Builds on (most cited first, 30 of 32)

- [PyTorch: An Imperative Style, High-Performance Deep Learning Library](https://mlsanity.com/paper/1912.01703/) (2019)
- [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)
- [Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fields](https://mlsanity.com/paper/2103.13415/) (2021)
- [Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network](https://mlsanity.com/paper/1609.05158/) (2016)
- [Block-NeRF: Scalable Large Scene Neural View Synthesis](https://mlsanity.com/paper/2202.05263/) (2022)
- [A Lip Sync Expert Is All You Need for Speech to Lip Generation In The Wild](https://mlsanity.com/paper/2008.10010/) (2020)
- [SadTalker: Learning Realistic 3D Motion Coefficients for Stylized Audio-Driven Single Image Talking Face Animation](https://mlsanity.com/paper/2211.12194/) (2022)
- [AD-NeRF: Audio Driven Neural Radiance Fields for Talking Head Synthesis](https://mlsanity.com/paper/2103.11078/) (2021)
- [Pose-Controllable Talking Face Generation by Implicitly Modularized Audio-Visual Representation](https://mlsanity.com/paper/2104.11116/) (2021)
- [EMOCA: Emotion Driven Monocular Face Capture and Animation](https://mlsanity.com/paper/2204.11312/) (2022)
- [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)
- [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)
- [EAMM: One-Shot Emotional Talking Face via Audio-Based Emotion-Aware Motion Model](https://mlsanity.com/paper/2205.15278/) (2022)
- [Audio2Head: Audio-driven One-shot Talking-head Generation with Natural Head Motion](https://mlsanity.com/paper/2107.09293/) (2021)
- [DiffTalk: Crafting Diffusion Models for Generalized Audio-Driven Portraits Animation](https://mlsanity.com/paper/2301.03786/) (2023)
- [Semantic-Aware Implicit Neural Audio-Driven Video Portrait Generation](https://mlsanity.com/paper/2201.07786/) (2022)
- [Learning Dynamic Facial Radiance Fields for Few-Shot Talking Head Synthesis](https://mlsanity.com/paper/2207.11770/) (2022)
- [FACIAL: Synthesizing Dynamic Talking Face with Implicit Attribute Learning](https://mlsanity.com/paper/2108.07938/) (2021)
- [DFA-NeRF: Personalized Talking Head Generation via Disentangled Face Attributes Neural Rendering](https://mlsanity.com/paper/2201.00791/) (2022)
- [DINet: Deformation Inpainting Network for Realistic Face Visually Dubbing on High Resolution Video](https://mlsanity.com/paper/2303.03988/) (2023)
- [LipSync3D: Data-Efficient Learning of Personalized 3D Talking Faces from Video using Pose and Lighting Normalization](https://mlsanity.com/paper/2106.04185/) (2021)
- [Imitating Arbitrary Talking Style for Realistic Audio-DrivenTalking Face Synthesis](https://mlsanity.com/paper/2111.00203/) (2021)
- [Speech Driven Video Editing via an Audio-Conditioned Diffusion Model](https://mlsanity.com/paper/2301.04474/) (2023)
- [Emotionally Enhanced Talking Face Generation](https://mlsanity.com/paper/2303.11548/) (2023)
- [Dynamic Neural Textures: Generating Talking-Face Videos with Continuously Controllable Expressions](https://mlsanity.com/paper/2204.06180/) (2022)
- [Synthesizing Photorealistic Virtual Humans Through Cross-modal Disentanglement](https://mlsanity.com/paper/2209.01320/) (2022)
- [Voice2Mesh: Cross-Modal 3D Face Model Generation from Voices](https://mlsanity.com/paper/2104.10299/) (2021)

## Abstract (arXiv)

The talking head generation recently attracted considerable attention due to its widespread application prospects, especially for digital avatars and 3D animation design. Inspired by this practical demand, several works explored Neural Radiance Fields (NeRF) to synthesize the talking heads. However, these methods based on NeRF face two challenges: (1) Difficulty in generating style-controllable talking heads. (2) Displacement artifacts around the neck in rendered images. To overcome these two challenges, we propose a novel generative paradigm textitEmbedded Representation Learning Network (ERLNet) with two learning stages. First, the textit audio-driven FLAME (ADF) module is constructed to produce facial expression and head pose sequences synchronized with content audio and style video. Second, given the sequence deduced by the ADF, one novel textitdual-branch fusion NeRF (DBF-NeRF) explores these contents to render the final images. Extensive empirical studies demonstrate that the collaboration of these two stages effectively facilitates our method to render a more realistic talking head than the existing algorithms.