# DaGAN++: Depth-Aware Generative Adversarial Network for Talking Head Video Generation

arXiv: https://arxiv.org/abs/2305.06225 · HTML: https://mlsanity.com/paper/2305.06225/

## Key facts

- Cited by 20 papers in the map (data through 14 Oct 2026).
- Builds on 55 of its 70 references that are in the map.
- First posted on arXiv 10 May 2023.

## Builds on (most cited first, 30 of 55)

- [Denoising Diffusion Probabilistic Models](https://mlsanity.com/paper/2006.11239/) (2020)
- [Swin Transformer: Hierarchical Vision Transformer using Shifted Windows](https://mlsanity.com/paper/2103.14030/) (2021)
- [Perceptual Losses for Real-Time Style Transfer and Super-Resolution](https://mlsanity.com/paper/1603.08155/) (2016)
- [VoxCeleb2: Deep Speaker Recognition](https://mlsanity.com/paper/1806.05622/) (2018)
- [Unsupervised Learning of Depth and Ego-Motion from Video](https://mlsanity.com/paper/1704.07813/) (2017)
- [VoxCeleb: a large-scale speaker identification dataset](https://mlsanity.com/paper/1706.08612/) (2017)
- [Deep Ordinal Regression Network for Monocular Depth Estimation](https://mlsanity.com/paper/1806.02446/) (2018)
- [First Order Motion Model for Image Animation](https://mlsanity.com/paper/2003.00196/) (2020)
- [MediaPipe: A Framework for Building Perception Pipelines](https://mlsanity.com/paper/1906.08172/) (2019)
- [Accurate 3D Face Reconstruction with Weakly-Supervised Learning: From Single Image to Image Set](https://mlsanity.com/paper/1903.08527/) (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)
- [MakeItTalk: Speaker-Aware Talking-Head Animation](https://mlsanity.com/paper/2004.12992/) (2020)
- [Pose-Controllable Talking Face Generation by Implicitly Modularized Audio-Visual Representation](https://mlsanity.com/paper/2104.11116/) (2021)
- [Few-Shot Adversarial Learning of Realistic Neural Talking Head Models](https://mlsanity.com/paper/1905.08233/) (2019)
- [The Sound of Pixels](https://mlsanity.com/paper/1804.03160/) (2018)
- [Motion Representations for Articulated Animation](https://mlsanity.com/paper/2104.11280/) (2021)
- [Disentangled and Controllable Face Image Generation via 3D Imitative-Contrastive Learning](https://mlsanity.com/paper/2004.11660/) (2020)
- [Consistent Video Depth Estimation](https://mlsanity.com/paper/2004.15021/) (2020)
- [Talking Face Generation by Adversarially Disentangled Audio-Visual Representation](https://mlsanity.com/paper/1807.07860/) (2018)
- [Thin-Plate Spline Motion Model for Image Animation](https://mlsanity.com/paper/2203.14367/) (2022)
- [Animating Arbitrary Objects via Deep Motion Transfer](https://mlsanity.com/paper/1812.08861/) (2018)
- [PIRenderer: Controllable Portrait Image Generation via Semantic Neural Rendering](https://mlsanity.com/paper/2109.08379/) (2021)
- [X2Face: A network for controlling face generation by using images, audio, and pose codes](https://mlsanity.com/paper/1807.10550/) (2018)
- [Depth-Aware Generative Adversarial Network for Talking Head Video Generation](https://mlsanity.com/paper/2203.06605/) (2022)
- [Latent Image Animator: Learning to Animate Images via Latent Space Navigation](https://mlsanity.com/paper/2203.09043/) (2022)
- [Depth from Videos in the Wild: Unsupervised Monocular Depth Learning from Unknown Cameras](https://mlsanity.com/paper/1904.04998/) (2019)
- [StyleHEAT: One-Shot High-Resolution Editable Talking Face Generation via Pre-trained StyleGAN](https://mlsanity.com/paper/2203.04036/) (2022)
- [Nonlinear 3D Face Morphable Model](https://mlsanity.com/paper/1804.03786/) (2018)
- [Audio2Head: Audio-driven One-shot Talking-head Generation with Natural Head Motion](https://mlsanity.com/paper/2107.09293/) (2021)

## Built on by (most cited first, 20 of 20)

- [HunyuanPortrait: Implicit Condition Control for Enhanced Portrait Animation](https://mlsanity.com/paper/2503.18860/) (2025)
- [MetaEarth: A Generative Foundation Model for Global-Scale Remote Sensing Image Generation](https://mlsanity.com/paper/2405.13570/) (2024)
- [Generative Artificial Intelligence: A Systematic Review and Applications](https://mlsanity.com/paper/2405.11029/) (2024)
- [Audio-visual Controlled Video Diffusion with Masked Selective State Spaces Modeling for Natural Talking Head Generation](https://mlsanity.com/paper/2504.02542/) (2025)
- [From Pixels to Portraits: A Comprehensive Survey of Talking Head Generation Techniques and Applications](https://mlsanity.com/paper/2308.16041/) (2023)
- [Instruct-Video2Avatar: Video-to-Avatar Generation with Instructions](https://mlsanity.com/paper/2306.02903/) (2023)
- [Generative Human Video Compression with Multi-granularity Temporal Trajectory Factorization](https://mlsanity.com/paper/2410.10171/) (2024)
- [Free-viewpoint Human Animation with Pose-correlated Reference Selection](https://mlsanity.com/paper/2412.17290/) (2024)
- [EDTalk++: Full Disentanglement for Controllable Talking Head Synthesis](https://mlsanity.com/paper/2508.13442/) (2025)
- [Replace Anyone in Videos](https://mlsanity.com/paper/2409.19911/) (2024)
- [DreamHead: Learning Spatial-Temporal Correspondence via Hierarchical Diffusion for Audio-driven Talking Head Synthesis](https://mlsanity.com/paper/2409.10281/) (2024)
- [JEAN: Joint Expression and Audio-guided NeRF-based Talking Face Generation](https://mlsanity.com/paper/2409.12156/) (2024)
- [Pleno-Generation: A Scalable Generative Face Video Compression Framework with Bandwidth Intelligence](https://mlsanity.com/paper/2502.17085/) (2025)
- [Generative Models at the Frontier of Compression: A Survey on Generative Face Video Coding](https://mlsanity.com/paper/2506.07369/) (2025)
- [AniArtAvatar: Animatable 3D Art Avatar from a Single Image](https://mlsanity.com/paper/2403.17631/) (2024)
- [One-Shot Pose-Driving Face Animation Platform](https://mlsanity.com/paper/2407.08949/) (2024)
- [Unmasking Puppeteers: Leveraging Biometric Leakage to Expose Impersonation in AI-Based Videoconferencing](https://mlsanity.com/paper/2510.03548/) (2025)
- [MoDiT: Learning Highly Consistent 3D Motion Coefficients with Diffusion Transformer for Talking Head Generation](https://mlsanity.com/paper/2507.05092/) (2025)
- [RealTalk: Realistic Emotion-Aware Lifelike Talking-Head Synthesis](https://mlsanity.com/paper/2508.12163/) (2025)
- [Inference-based GAN Video Generation](https://mlsanity.com/paper/2512.21776/) (2025)

## Abstract (arXiv)

Predominant techniques on talking head generation largely depend on 2D information, including facial appearances and motions from input face images. Nevertheless, dense 3D facial geometry, such as pixel-wise depth, plays a critical role in constructing accurate 3D facial structures and suppressing complex background noises for generation. However, dense 3D annotations for facial videos is prohibitively costly to obtain. In this work, firstly, we present a novel self-supervised method for learning dense 3D facial geometry (ie, depth) from face videos, without requiring camera parameters and 3D geometry annotations in training. We further propose a strategy to learn pixel-level uncertainties to perceive more reliable rigid-motion pixels for geometry learning. Secondly, we design an effective geometry-guided facial keypoint estimation module, providing accurate keypoints for generating motion fields. Lastly, we develop a 3D-aware cross-modal (ie, appearance and depth) attention mechanism, which can be applied to each generation layer, to capture facial geometries in a coarse-to-fine manner. Extensive experiments are conducted on three challenging benchmarks (ie, VoxCeleb1, VoxCeleb2, and HDTF). The results demonstrate that our proposed framework can generate highly realistic-looking reenacted talking videos, with new state-of-the-art performances established on these benchmarks. The codes and trained models are publicly available on the GitHub project page at https://github.com/harlanhong/CVPR2022-DaGAN