# DiffusionAvatars: Deferred Diffusion for High-fidelity 3D Head Avatars

arXiv: https://arxiv.org/abs/2311.18635 · HTML: https://mlsanity.com/paper/2311.18635/

## Key facts

- Cited by 42 papers in the map (data through 14 Oct 2026).
- Builds on 72 of its 100 references that are in the map.
- First posted on arXiv 30 Nov 2023.

## Builds on (most cited first, 30 of 72)

- [Denoising Diffusion Probabilistic Models](https://mlsanity.com/paper/2006.11239/) (2020)
- [High-Resolution Image Synthesis with Latent Diffusion Models](https://mlsanity.com/paper/2112.10752/) (2021)
- [The Unreasonable Effectiveness of Deep Features as a Perceptual Metric](https://mlsanity.com/paper/1801.03924/) (2018)
- [A Style-Based Generator Architecture for Generative Adversarial Networks](https://mlsanity.com/paper/1812.04948/) (2018)
- [Generative Adversarial Networks](https://mlsanity.com/paper/2203.00667/) (2022)
- [Adding Conditional Control to Text-to-Image Diffusion Models](https://mlsanity.com/paper/2302.05543/) (2023)
- [Taming Transformers for High-Resolution Image Synthesis](https://mlsanity.com/paper/2012.09841/) (2020)
- [DreamFusion: Text-to-3D using 2D Diffusion](https://mlsanity.com/paper/2209.14988/) (2022)
- [Video Diffusion Models](https://mlsanity.com/paper/2204.03458/) (2022)
- [Consistency Models](https://mlsanity.com/paper/2303.01469/) (2023)
- [Imagen Video: High Definition Video Generation with Diffusion Models](https://mlsanity.com/paper/2210.02303/) (2022)
- [Make-A-Video: Text-to-Video Generation without Text-Video Data](https://mlsanity.com/paper/2209.14792/) (2022)
- [Zero-1-to-3: Zero-shot One Image to 3D Object](https://mlsanity.com/paper/2303.11328/) (2023)
- [Align your Latents: High-Resolution Video Synthesis with Latent Diffusion Models](https://mlsanity.com/paper/2304.08818/) (2023)
- [IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models](https://mlsanity.com/paper/2308.06721/) (2023)
- [T2I-Adapter: Learning Adapters to Dig out More Controllable Ability for Text-to-Image Diffusion Models](https://mlsanity.com/paper/2302.08453/) (2023)
- [Efficient Geometry-aware 3D Generative Adversarial Networks](https://mlsanity.com/paper/2112.07945/) (2021)
- [Alias-Free Generative Adversarial Networks](https://mlsanity.com/paper/2106.12423/) (2021)
- [Tune-A-Video: One-Shot Tuning of Image Diffusion Models for Text-to-Video Generation](https://mlsanity.com/paper/2212.11565/) (2022)
- [Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation](https://mlsanity.com/paper/2008.00951/) (2020)
- [On Distillation of Guided Diffusion Models](https://mlsanity.com/paper/2210.03142/) (2022)
- [Designing an Encoder for StyleGAN Image Manipulation](https://mlsanity.com/paper/2102.02766/) (2021)
- [Learning an Animatable Detailed 3D Face Model from In-The-Wild Images](https://mlsanity.com/paper/2012.04012/) (2020)
- [Dynamic Neural Radiance Fields for Monocular 4D Facial Avatar Reconstruction](https://mlsanity.com/paper/2012.03065/) (2020)
- [One-Shot Free-View Neural Talking-Head Synthesis for Video Conferencing](https://mlsanity.com/paper/2011.15126/) (2020)
- [TokenFlow: Consistent Diffusion Features for Consistent Video Editing](https://mlsanity.com/paper/2307.10373/) (2023)
- [Modular Primitives for High-Performance Differentiable Rendering](https://mlsanity.com/paper/2011.03277/) (2020)
- [LAVIE: High-Quality Video Generation with Cascaded Latent Diffusion Models](https://mlsanity.com/paper/2309.15103/) (2023)
- [Common Diffusion Noise Schedules and Sample Steps are Flawed](https://mlsanity.com/paper/2305.08891/) (2023)
- [Rodin: A Generative Model for Sculpting 3D Digital Avatars Using Diffusion](https://mlsanity.com/paper/2212.06135/) (2022)

## Built on by (most cited first, 30 of 42)

- [Arc2Face: A Foundation Model for ID-Consistent Human Faces](https://mlsanity.com/paper/2403.11641/) (2024)
- [Avat3r: Large Animatable Gaussian Reconstruction Model for High-fidelity 3D Head Avatars](https://mlsanity.com/paper/2502.20220/) (2025)
- [CAP4D: Creating Animatable 4D Portrait Avatars with Morphable Multi-View Diffusion Models](https://mlsanity.com/paper/2412.12093/) (2024)
- [HeadGAP: Few-Shot 3D Head Avatar via Generalizable Gaussian Priors](https://mlsanity.com/paper/2408.06019/) (2024)
- [FLOAT: Generative Motion Latent Flow Matching for Audio-driven Talking Portrait](https://mlsanity.com/paper/2412.01064/) (2024)
- [MonoNPHM: Dynamic Head Reconstruction from Monocular Videos](https://mlsanity.com/paper/2312.06740/) (2023)
- [HeadStudio: Text to Animatable Head Avatars with 3D Gaussian Splatting](https://mlsanity.com/paper/2402.06149/) (2024)
- [Mani-GS: Gaussian Splatting Manipulation with Triangular Mesh](https://mlsanity.com/paper/2405.17811/) (2024)
- [Gaussian Eigen Models for Human Heads](https://mlsanity.com/paper/2407.04545/) (2024)
- [Pixel3DMM: Versatile Screen-Space Priors for Single-Image 3D Face Reconstruction](https://mlsanity.com/paper/2505.00615/) (2025)
- [PSAvatar: A Point-based Shape Model for Real-Time Head Avatar Animation with 3D Gaussian Splatting](https://mlsanity.com/paper/2401.12900/) (2024)
- [PERSE: Personalized 3D Generative Avatars from A Single Portrait](https://mlsanity.com/paper/2412.21206/) (2024)
- [Synthetic Prior for Few-Shot Drivable Head Avatar Inversion](https://mlsanity.com/paper/2501.06903/) (2025)
- [Zero-1-to-A: Zero-Shot One Image to Animatable Head Avatars Using Video Diffusion](https://mlsanity.com/paper/2503.15851/) (2025)
- [DNF: Unconditional 4D Generation with Dictionary-based Neural Fields](https://mlsanity.com/paper/2412.05161/) (2024)
- [ConsistentAvatar: Learning to Diffuse Fully Consistent Talking Head Avatar with Temporal Guidance](https://mlsanity.com/paper/2411.15436/) (2024)
- [GHOST 2.0: generative high-fidelity one shot transfer of heads](https://mlsanity.com/paper/2502.18417/) (2025)
- [MagicPortrait: Temporally Consistent Face Reenactment with 3D Geometric Guidance](https://mlsanity.com/paper/2504.21497/) (2025)
- [DeX-Portrait: Disentangled and Expressive Portrait Animation via Explicit and Latent Motion Representations](https://mlsanity.com/paper/2512.15524/) (2025)
- [Controlling Avatar Diffusion with Learnable Gaussian Embedding](https://mlsanity.com/paper/2503.15809/) (2025)
- [Revealing Directions for Text-guided 3D Face Editing](https://mlsanity.com/paper/2410.04965/) (2024)
- [TalkingPose: Efficient Face and Gesture Animation with Feedback-guided Diffusion Model](https://mlsanity.com/paper/2512.00909/) (2025)
- [TexAvatars : Hybrid Texel-3D Representations for Stable Rigging of Photorealistic Gaussian Head Avatars](https://mlsanity.com/paper/2512.21099/) (2025)
- [Towards High-Fidelity 3D Portrait Generation with Rich Details by Cross-View Prior-Aware Diffusion](https://mlsanity.com/paper/2411.10369/) (2024)
- [LightHeadEd: Relightable & Editable Head Avatars from a Smartphone](https://mlsanity.com/paper/2504.09671/) (2025)
- [FactorPortrait: Controllable Portrait Animation via Disentangled Expression, Pose, and Viewpoint](https://mlsanity.com/paper/2512.11645/) (2025)
- [Pix2NPHM: Learning to Regress NPHM Reconstructions From a Single Image](https://mlsanity.com/paper/2512.17773/) (2025)
- [Spherical Geometry Diffusion: Generating High-quality 3D Face Geometry via Sphere-anchored Representations](https://mlsanity.com/paper/2601.13371/) (2026)
- [Multi-view Consistent 3D Gaussian Head Avatars 'without' Multi-view Generation](https://mlsanity.com/paper/2605.25220/) (2026)
- [Multimodal Conditional 3D Face Geometry Generation](https://mlsanity.com/paper/2407.01074/) (2024)

## Abstract (arXiv)

DiffusionAvatars synthesizes a high-fidelity 3D head avatar of a person, offering intuitive control over both pose and expression. We propose a diffusion-based neural renderer that leverages generic 2D priors to produce compelling images of faces. For coarse guidance of the expression and head pose, we render a neural parametric head model (NPHM) from the target viewpoint, which acts as a proxy geometry of the person. Additionally, to enhance the modeling of intricate facial expressions, we condition DiffusionAvatars directly on the expression codes obtained from NPHM via cross-attention. Finally, to synthesize consistent surface details across different viewpoints and expressions, we rig learnable spatial features to the head's surface via TriPlane lookup in NPHM's canonical space. We train DiffusionAvatars on RGB videos and corresponding fitted NPHM meshes of a person and test the obtained avatars in both self-reenactment and animation scenarios. Our experiments demonstrate that DiffusionAvatars generates temporally consistent and visually appealing videos for novel poses and expressions of a person, outperforming existing approaches.