# A Hierarchical Representation Network for Accurate and Detailed Face Reconstruction from In-The-Wild Images

arXiv: https://arxiv.org/abs/2302.14434 · HTML: https://mlsanity.com/paper/2302.14434/

## Key facts

- Cited by 43 papers in the map (data through 14 Oct 2026).
- Builds on 33 of its 58 references that are in the map.
- First posted on arXiv 28 Feb 2023.

## Builds on (most cited first, 30 of 33)

- [A Style-Based Generator Architecture for Generative Adversarial Networks](https://mlsanity.com/paper/1812.04948/) (2018)
- [Image-to-Image Translation with Conditional Adversarial Networks](https://mlsanity.com/paper/1611.07004/) (2016)
- [Perceptual Losses for Real-Time Style Transfer and Super-Resolution](https://mlsanity.com/paper/1603.08155/) (2016)
- [Open3D: A Modern Library for 3D Data Processing](https://mlsanity.com/paper/1801.09847/) (2018)
- [Accurate 3D Face Reconstruction with Weakly-Supervised Learning: From Single Image to Image Set](https://mlsanity.com/paper/1903.08527/) (2019)
- [Learning an Animatable Detailed 3D Face Model from In-The-Wild Images](https://mlsanity.com/paper/2012.04012/) (2020)
- [Modular Primitives for High-Performance Differentiable Rendering](https://mlsanity.com/paper/2011.03277/) (2020)
- [FaceScape: a Large-scale High Quality 3D Face Dataset and Detailed Riggable 3D Face Prediction](https://mlsanity.com/paper/2003.13989/) (2020)
- [Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network](https://mlsanity.com/paper/1803.07835/) (2018)
- [Learning to Regress 3D Face Shape and Expression from an Image without 3D Supervision](https://mlsanity.com/paper/1905.06817/) (2019)
- [Towards Metrical Reconstruction of Human Faces](https://mlsanity.com/paper/2204.06607/) (2022)
- [MoFA: Model-based Deep Convolutional Face Autoencoder for Unsupervised Monocular Reconstruction](https://mlsanity.com/paper/1703.10580/) (2017)
- [Nonlinear 3D Face Morphable Model](https://mlsanity.com/paper/1804.03786/) (2018)
- [GANFIT: Generative Adversarial Network Fitting for High Fidelity 3D Face Reconstruction](https://mlsanity.com/paper/1902.05978/) (2019)
- [Regressing Robust and Discriminative 3D Morphable Models with a very Deep Neural Network](https://mlsanity.com/paper/1612.04904/) (2016)
- [Unsupervised Training for 3D Morphable Model Regression](https://mlsanity.com/paper/1806.06098/) (2018)
- [Towards High-fidelity Nonlinear 3D Face Morphable Model](https://mlsanity.com/paper/1904.04933/) (2019)
- [AvatarMe: Realistically Renderable 3D Facial Reconstruction "in-the-wild"](https://mlsanity.com/paper/2003.13845/) (2020)
- [Learning Detailed Face Reconstruction from a Single Image](https://mlsanity.com/paper/1611.05053/) (2016)
- [Unrestricted Facial Geometry Reconstruction Using Image-to-Image Translation](https://mlsanity.com/paper/1703.10131/) (2017)
- [Boosting Semantic Human Matting with Coarse Annotations](https://mlsanity.com/paper/2004.04955/) (2020)
- [Towards High Fidelity Monocular Face Reconstruction with Rich Reflectance using Self-supervised Learning and Ray Tracing](https://mlsanity.com/paper/2103.15432/) (2021)
- [MVF-Net: Multi-View 3D Face Morphable Model Regression](https://mlsanity.com/paper/1904.04473/) (2019)
- [3D Face Morphable Models "In-the-Wild"](https://mlsanity.com/paper/1701.05360/) (2017)
- [Photo-Realistic Facial Details Synthesis from Single Image](https://mlsanity.com/paper/1903.10873/) (2019)
- [FaceScape: 3D Facial Dataset and Benchmark for Single-View 3D Face Reconstruction](https://mlsanity.com/paper/2111.01082/) (2021)
- [Fast-GANFIT: Generative Adversarial Network for High Fidelity 3D Face Reconstruction](https://mlsanity.com/paper/2105.07474/) (2021)
- [REALY: Rethinking the Evaluation of 3D Face Reconstruction](https://mlsanity.com/paper/2203.09729/) (2022)
- [SADRNet: Self-Aligned Dual Face Regression Networks for Robust 3D Dense Face Alignment and Reconstruction](https://mlsanity.com/paper/2106.03021/) (2021)
- [Self-supervised Learning of Detailed 3D Face Reconstruction](https://mlsanity.com/paper/1910.11791/) (2019)

## Built on by (most cited first, 30 of 43)

- [3D Face Reconstruction with the Geometric Guidance of Facial Part Segmentation](https://mlsanity.com/paper/2312.00311/) (2023)
- [MonoNPHM: Dynamic Head Reconstruction from Monocular Videos](https://mlsanity.com/paper/2312.06740/) (2023)
- [VOODOO 3D: Volumetric Portrait Disentanglement for One-Shot 3D Head Reenactment](https://mlsanity.com/paper/2312.04651/) (2023)
- [HiFace: High-Fidelity 3D Face Reconstruction by Learning Static and Dynamic Details](https://mlsanity.com/paper/2303.11225/) (2023)
- [Generalizable One-shot Neural Head Avatar](https://mlsanity.com/paper/2306.08768/) (2023)
- [Towards Realistic Generative 3D Face Models](https://mlsanity.com/paper/2304.12483/) (2023)
- [3D Face Tracking from 2D Video through Iterative Dense UV to Image Flow](https://mlsanity.com/paper/2404.09819/) (2024)
- [MoSAR: Monocular Semi-Supervised Model for Avatar Reconstruction using Differentiable Shading](https://mlsanity.com/paper/2312.13091/) (2023)
- [BAGS: Building Animatable Gaussian Splatting from a Monocular Video with Diffusion Priors](https://mlsanity.com/paper/2403.11427/) (2024)
- [ExpCLIP: Bridging Text and Facial Expressions via Semantic Alignment](https://mlsanity.com/paper/2308.14448/) (2023)
- [What You See is What You GAN: Rendering Every Pixel for High-Fidelity Geometry in 3D GANs](https://mlsanity.com/paper/2401.02411/) (2024)
- [Implicit Shape and Appearance Priors for Few-Shot Full Head Reconstruction](https://mlsanity.com/paper/2310.08784/) (2023)
- [BiTT: Bi-directional Texture Reconstruction of Interacting Two Hands from a Single Image](https://mlsanity.com/paper/2403.08262/) (2024)
- [Topo4D: Topology-Preserving Gaussian Splatting for High-Fidelity 4D Head Capture](https://mlsanity.com/paper/2406.00440/) (2024)
- [SHeaP: Self-Supervised Head Geometry Predictor Learned via 2D Gaussians](https://mlsanity.com/paper/2504.12292/) (2025)
- [SplatFace: Gaussian Splat Face Reconstruction Leveraging an Optimizable Surface](https://mlsanity.com/paper/2403.18784/) (2024)
- [FreeUV: Ground-Truth-Free Realistic Facial UV Texture Recovery via Cross-Assembly Inference Strategy](https://mlsanity.com/paper/2503.17197/) (2025)
- [A Perceptual Shape Loss for Monocular 3D Face Reconstruction](https://mlsanity.com/paper/2310.19580/) (2023)
- [High-Quality Mesh Blendshape Generation from Face Videos via Neural Inverse Rendering](https://mlsanity.com/paper/2401.08398/) (2024)
- [VGG-Tex: A Vivid Geometry-Guided Facial Texture Estimation Model for High Fidelity Monocular 3D Face Reconstruction](https://mlsanity.com/paper/2409.09740/) (2024)
- [FitDiff: Robust monocular 3D facial shape and reflectance estimation using Diffusion Models](https://mlsanity.com/paper/2312.04465/) (2023)
- [FreeAvatar: Robust 3D Facial Animation Transfer by Learning an Expression Foundation Model](https://mlsanity.com/paper/2409.13180/) (2024)
- [SEREP: Semantic Facial Expression Representation for Robust In-the-Wild Capture and Retargeting](https://mlsanity.com/paper/2412.14371/) (2024)
- [Exploiting Multiple Representations: 3D Face Biometrics Fusion with Application to Surveillance](https://mlsanity.com/paper/2504.18886/) (2025)
- [VGGTFace: Topologically Consistent Facial Geometry Reconstruction in the Wild](https://mlsanity.com/paper/2511.20366/) (2025)
- [Disjoint Pose and Shape for 3D Face Reconstruction](https://mlsanity.com/paper/2308.13903/) (2023)
- [Unified Physical-Digital Attack Detection Challenge](https://mlsanity.com/paper/2404.06211/) (2024)
- [Fine-Grained Multi-View Hand Reconstruction Using Inverse Rendering](https://mlsanity.com/paper/2407.05680/) (2024)
- [High-Fidelity Facial Albedo Estimation via Texture Quantization](https://mlsanity.com/paper/2406.13149/) (2024)
- [High-Quality Facial Albedo Generation for 3D Face Reconstruction from a Single Image using a Coarse-to-Fine Approach](https://mlsanity.com/paper/2506.13233/) (2025)

## Abstract (arXiv)

Limited by the nature of the low-dimensional representational capacity of 3DMM, most of the 3DMM-based face reconstruction (FR) methods fail to recover high-frequency facial details, such as wrinkles, dimples, etc. Some attempt to solve the problem by introducing detail maps or non-linear operations, however, the results are still not vivid. To this end, we in this paper present a novel hierarchical representation network (HRN) to achieve accurate and detailed face reconstruction from a single image. Specifically, we implement the geometry disentanglement and introduce the hierarchical representation to fulfill detailed face modeling. Meanwhile, 3D priors of facial details are incorporated to enhance the accuracy and authenticity of the reconstruction results. We also propose a de-retouching module to achieve better decoupling of the geometry and appearance. It is noteworthy that our framework can be extended to a multi-view fashion by considering detail consistency of different views. Extensive experiments on two single-view and two multi-view FR benchmarks demonstrate that our method outperforms the existing methods in both reconstruction accuracy and visual effects. Finally, we introduce a high-quality 3D face dataset FaceHD-100 to boost the research of high-fidelity face reconstruction. The project homepage is at https://younglbw.github.io/HRN-homepage/.