# LPFF: A Portrait Dataset for Face Generators Across Large Poses

arXiv: https://arxiv.org/abs/2303.14407 · HTML: https://mlsanity.com/paper/2303.14407/

## Key facts

- Cited by 22 papers in the map (data through 14 Oct 2026).
- Builds on 42 of its 57 references that are in the map.
- First posted on arXiv 25 Mar 2023.

## Builds on (most cited first, 30 of 42)

- [A Style-Based Generator Architecture for Generative Adversarial Networks](https://mlsanity.com/paper/1812.04948/) (2018)
- [Analyzing and Improving the Image Quality of StyleGAN](https://mlsanity.com/paper/1912.04958/) (2019)
- [Progressive Growing of GANs for Improved Quality, Stability, and Variation](https://mlsanity.com/paper/1710.10196/) (2017)
- [Large Scale GAN Training for High Fidelity Natural Image Synthesis](https://mlsanity.com/paper/1809.11096/) (2018)
- [Improved Training of Wasserstein GANs](https://mlsanity.com/paper/1704.00028/) (2017)
- [Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks](https://mlsanity.com/paper/1511.06434/) (2015)
- [Efficient Geometry-aware 3D Generative Adversarial Networks](https://mlsanity.com/paper/2112.07945/) (2021)
- [Training Generative Adversarial Networks with Limited Data](https://mlsanity.com/paper/2006.06676/) (2020)
- [Alias-Free Generative Adversarial Networks](https://mlsanity.com/paper/2106.12423/) (2021)
- [StyleCLIP: Text-Driven Manipulation of StyleGAN Imagery](https://mlsanity.com/paper/2103.17249/) (2021)
- [Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks](https://mlsanity.com/paper/1604.02878/) (2016)
- [pi-GAN: Periodic Implicit Generative Adversarial Networks for 3D-Aware Image Synthesis](https://mlsanity.com/paper/2012.00926/) (2020)
- [Interpreting the Latent Space of GANs for Semantic Face Editing](https://mlsanity.com/paper/1907.10786/) (2019)
- [GRAF: Generative Radiance Fields for 3D-Aware Image Synthesis](https://mlsanity.com/paper/2007.02442/) (2020)
- [How far are we from solving the 2D & 3D Face Alignment problem? (and a dataset of 230,000 3D facial landmarks)](https://mlsanity.com/paper/1703.07332/) (2017)
- [Accurate 3D Face Reconstruction with Weakly-Supervised Learning: From Single Image to Image Set](https://mlsanity.com/paper/1903.08527/) (2019)
- [StyleNeRF: A Style-based 3D-Aware Generator for High-resolution Image Synthesis](https://mlsanity.com/paper/2110.08985/) (2021)
- [StyleFlow: Attribute-conditioned Exploration of StyleGAN-Generated Images using Conditional Continuous Normalizing Flows](https://mlsanity.com/paper/2008.02401/) (2020)
- [StyleSDF: High-Resolution 3D-Consistent Image and Geometry Generation](https://mlsanity.com/paper/2112.11427/) (2021)
- [GRAM: Generative Radiance Manifolds for 3D-Aware Image Generation](https://mlsanity.com/paper/2112.08867/) (2021)
- [FaceScape: a Large-scale High Quality 3D Face Dataset and Detailed Riggable 3D Face Prediction](https://mlsanity.com/paper/2003.13989/) (2020)
- [Escaping Plato's Cave: 3D Shape From Adversarial Rendering](https://mlsanity.com/paper/1811.11606/) (2018)
- [BlockGAN: Learning 3D Object-aware Scene Representations from Unlabelled Images](https://mlsanity.com/paper/2002.08988/) (2020)
- [CIPS-3D: A 3D-Aware Generator of GANs Based on Conditionally-Independent Pixel Synthesis](https://mlsanity.com/paper/2110.09788/) (2021)
- [VoxGRAF: Fast 3D-Aware Image Synthesis with Sparse Voxel Grids](https://mlsanity.com/paper/2206.07695/) (2022)
- [Visual Object Networks: Image Generation with Disentangled 3D Representation](https://mlsanity.com/paper/1812.02725/) (2018)
- [FENeRF: Face Editing in Neural Radiance Fields](https://mlsanity.com/paper/2111.15490/) (2021)
- [EpiGRAF: Rethinking training of 3D GANs](https://mlsanity.com/paper/2206.10535/) (2022)
- [Multiface: A Dataset for Neural Face Rendering](https://mlsanity.com/paper/2207.11243/) (2022)
- [GIRAFFE HD: A High-Resolution 3D-aware Generative Model](https://mlsanity.com/paper/2203.14954/) (2022)

## Built on by (most cited first, 22 of 22)

- [SphereHead: Stable 3D Full-head Synthesis with Spherical Tri-plane Representation](https://mlsanity.com/paper/2404.05680/) (2024)
- [FaceLift: Learning Generalizable Single Image 3D Face Reconstruction from Synthetic Heads](https://mlsanity.com/paper/2412.17812/) (2024)
- [Gaussian Splatting Decoder for 3D-aware Generative Adversarial Networks](https://mlsanity.com/paper/2404.10625/) (2024)
- [3DPortraitGAN: Learning One-Quarter Headshot 3D GANs from a Single-View Portrait Dataset with Diverse Body Poses](https://mlsanity.com/paper/2307.14770/) (2023)
- [FreeUV: Ground-Truth-Free Realistic Facial UV Texture Recovery via Cross-Assembly Inference Strategy](https://mlsanity.com/paper/2503.17197/) (2025)
- [PanoLAM: Large Avatar Model for Gaussian Full-Head Synthesis from One-shot Unposed Image](https://mlsanity.com/paper/2509.07552/) (2025)
- [EFHQ: Multi-purpose ExtremePose-Face-HQ dataset](https://mlsanity.com/paper/2312.17205/) (2023)
- [HyPlaneHead: Rethinking Tri-plane-like Representations in Full-Head Image Synthesis](https://mlsanity.com/paper/2509.16748/) (2025)
- [Synthetic to Authentic: Transferring Realism to 3D Face Renderings for Boosting Face Recognition](https://mlsanity.com/paper/2407.07627/) (2024)
- [Dual Encoder GAN Inversion for High-Fidelity 3D Head Reconstruction from Single Images](https://mlsanity.com/paper/2409.20530/) (2024)
- [DiffusionReward: Enhancing Blind Face Restoration through Reward Feedback Learning](https://mlsanity.com/paper/2505.17910/) (2025)
- [Head3D: Complete 3D Head Generation via Tri-plane Feature Distillation](https://mlsanity.com/paper/2303.15892/) (2023)
- [Multi-view Inversion for 3D-aware Generative Adversarial Networks](https://mlsanity.com/paper/2312.05330/) (2023)
- [FaceLift: Semi-supervised 3D Facial Landmark Localization](https://mlsanity.com/paper/2405.19646/) (2024)
- [Text-based Animatable 3D Avatars with Morphable Model Alignment](https://mlsanity.com/paper/2504.15835/) (2025)
- [Condition Matters in Full-head 3D GANs](https://mlsanity.com/paper/2602.07198/) (2026)
- [Democratizing the Creation of Animatable Facial Avatars](https://mlsanity.com/paper/2401.16534/) (2024)
- [AlphaFace: High Fidelity and Real-time Face Swapper Robust to Facial Pose](https://mlsanity.com/paper/2601.16429/) (2026)
- [CylinderPlane: Nested Cylinder Representation for 3D-aware Image Generation](https://mlsanity.com/paper/2507.15606/) (2025)
- [Densemarks: Learning Canonical Embeddings for Human Heads Images via Point Tracks](https://mlsanity.com/paper/2511.02830/) (2025)
- [WarpGAN: Warping-Guided 3D GAN Inversion with Style-Based Novel View Inpainting](https://mlsanity.com/paper/2511.08178/) (2025)
- [OMGTex: One-stage Multi-style Facial Texture Reconstruction without Geometry Guidance](https://mlsanity.com/paper/2605.25778/) (2026)

## Abstract (arXiv)

The creation of 2D realistic facial images and 3D face shapes using generative networks has been a hot topic in recent years. Existing face generators exhibit exceptional performance on faces in small to medium poses (with respect to frontal faces) but struggle to produce realistic results for large poses. The distorted rendering results on large poses in 3D-aware generators further show that the generated 3D face shapes are far from the distribution of 3D faces in reality. We find that the above issues are caused by the training dataset's pose imbalance. In this paper, we present LPFF, a large-pose Flickr face dataset comprised of 19,590 high-quality real large-pose portrait images. We utilize our dataset to train a 2D face generator that can process large-pose face images, as well as a 3D-aware generator that can generate realistic human face geometry. To better validate our pose-conditional 3D-aware generators, we develop a new FID measure to evaluate the 3D-level performance. Through this novel FID measure and other experiments, we show that LPFF can help 2D face generators extend their latent space and better manipulate the large-pose data, and help 3D-aware face generators achieve better view consistency and more realistic 3D reconstruction results.