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uniface/docs/datasets.md
Yakhyokhuja Valikhujaev 02c77ce5db feat: Add head pose estimation model (#99) 
* feat: Add Head Pose Estimation  with 6 different models

* chore: Update jupyter notebook examples

* docs: Update head pose estimation related docs
2026-03-26 22:57:05 +09:00

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# Datasets
Overview of all training datasets and evaluation benchmarks used by UniFace models.
---
## Quick Reference
| Task | Dataset | Scale | Models |
| ----------- | ------------------------------------------------ | ---------------------- | ------------------------------------------- |
| Detection | [WIDER FACE](#wider-face) | 32K images | RetinaFace, SCRFD, YOLOv5-Face, YOLOv8-Face |
| Recognition | [MS1MV2](#ms1mv2) | 5.8M images, 85.7K IDs | MobileFace, SphereFace |
| Recognition | [WebFace600K](#webface600k) | 600K images | ArcFace |
| Recognition | [WebFace4M / WebFace12M](#webface4m--webface12m) | 4M / 12M images | AdaFace |
| Gaze | [Gaze360](#gaze360) | 238 subjects | MobileGaze |
| Parsing | [CelebAMask-HQ](#celebamask-hq) | 30K images | BiSeNet |
| Attributes | [CelebA](#celeba) | 200K images | AgeGender |
| Attributes | [FairFace](#fairface) | Balanced demographics | FairFace |
| Attributes | [AffectNet](#affectnet) | Emotion labels | Emotion |
---
## Training Datasets
### Face Detection
#### WIDER FACE
Large-scale face detection benchmark with images across 61 event categories. Contains faces with a high degree of variability in scale, pose, occlusion, expression, and illumination.
| Property | Value |
| -------- | ------------------------------------------- |
| Images | ~32,000 (train/val/test split) |
| Faces | ~394,000 annotated |
| Subsets | Easy, Medium, Hard |
| Used by | RetinaFace, SCRFD, YOLOv5-Face, YOLOv8-Face |
!!! info "Download & References"
**Paper**: [WIDER FACE: A Face Detection Benchmark](https://arxiv.org/abs/1511.06523)
**Download**: [http://shuoyang1213.me/WIDERFACE/](http://shuoyang1213.me/WIDERFACE/)
---
### Face Recognition
#### MS1MV2
Refined version of the MS-Celeb-1M dataset, cleaned by InsightFace. Widely used for training face recognition models.
| Property | Value |
| ---------- | ------------------------------ |
| Identities | 85.7K |
| Images | 5.8M |
| Format | Aligned and cropped to 112x112 |
| Used by | MobileFace, SphereFace |
!!! info "Download"
**Kaggle (aligned 112x112)**: [ms1m-arcface-dataset](https://www.kaggle.com/datasets/yakhyokhuja/ms1m-arcface-dataset) (from InsightFace)
**Training code**: [yakhyo/face-recognition](https://github.com/yakhyo/face-recognition)
---
#### WebFace600K
Medium-scale face recognition dataset from the WebFace series.
| Property | Value |
| -------- | ------- |
| Images | ~600K |
| Used by | ArcFace |
!!! info "Source"
**Origin**: [InsightFace](https://github.com/deepinsight/insightface)
**Paper**: [ArcFace: Additive Angular Margin Loss for Deep Face Recognition](https://arxiv.org/abs/1801.07698)
---
#### WebFace4M / WebFace12M
Large-scale face recognition datasets from the WebFace260M collection. Used for training AdaFace models with adaptive quality-aware margin.
| Property | WebFace4M | WebFace12M |
| -------- | ------------- | -------------- |
| Images | ~4M | ~12M |
| Used by | AdaFace IR_18 | AdaFace IR_101 |
!!! info "Source"
**Paper**: [AdaFace: Quality Adaptive Margin for Face Recognition](https://arxiv.org/abs/2204.00964)
**Original code**: [mk-minchul/AdaFace](https://github.com/mk-minchul/AdaFace)
---
#### CASIA-WebFace
Smaller-scale face recognition dataset suitable for academic research and lighter training runs.
| Property | Value |
| ---------- | ------------------------------ |
| Identities | 10.6K |
| Images | 491K |
| Format | Aligned and cropped to 112x112 |
| Used by | Alternative training set |
!!! info "Download"
**Kaggle (aligned 112x112)**: [webface-112x112](https://www.kaggle.com/datasets/yakhyokhuja/webface-112x112) (from OpenSphere)
---
#### VGGFace2
Large-scale dataset with wide variations in pose, age, illumination, ethnicity, and profession.
| Property | Value |
| ---------- | ------------------------------ |
| Identities | 8.6K |
| Images | 3.1M |
| Format | Aligned and cropped to 112x112 |
| Used by | Alternative training set |
!!! info "Download"
**Kaggle (aligned 112x112)**: [vggface2-112x112](https://www.kaggle.com/datasets/yakhyokhuja/vggface2-112x112) (from OpenSphere)
---
### Gaze Estimation
#### Gaze360
Large-scale gaze estimation dataset collected in indoor and outdoor environments with diverse head poses and wide gaze ranges (up to 360 degrees).
| Property | Value |
| ----------- | --------------------- |
| Subjects | 238 |
| Environment | Indoor and outdoor |
| Used by | All MobileGaze models |
!!! info "Download & Preprocessing"
**Download**: [gaze360.csail.mit.edu/download.php](https://gaze360.csail.mit.edu/download.php)
**Preprocessing**: [GazeHub - Gaze360](https://phi-ai.buaa.edu.cn/Gazehub/3D-dataset/#gaze360)
!!! note "UniFace Models"
All MobileGaze models shipped with UniFace are trained exclusively on Gaze360 for 200 epochs.
**Dataset structure:**
```
data/
└── Gaze360/
├── Image/
└── Label/
```
---
#### MPIIFaceGaze
Dataset for appearance-based gaze estimation from laptop webcam images of participants during everyday laptop usage. Supported by the gaze estimation training code but not used for the UniFace pretrained weights.
| Property | Value |
| ----------- | ---------------------------------------- |
| Subjects | 15 |
| Environment | Everyday laptop usage |
| Used by | Supported (not used for UniFace weights) |
!!! info "Download & Preprocessing"
**Download**: [MPIIFaceGaze download page](https://www.mpi-inf.mpg.de/departments/computer-vision-and-machine-learning/research/gaze-based-human-computer-interaction/its-written-all-over-your-face-full-face-appearance-based-gaze-estimation)
**Preprocessing**: [GazeHub - MPIIFaceGaze](https://phi-ai.buaa.edu.cn/Gazehub/3D-dataset/#mpiifacegaze)
**Dataset structure:**
```
data/
└── MPIIFaceGaze/
├── Image/
└── Label/
```
---
### Head Pose Estimation
#### 300W-LP
Large-scale synthesized face dataset with large pose variations, generated from 300W by face profiling. Used for training head pose estimation models.
| Property | Value |
| ----------- | ----------------------------- |
| Images | ~122,000 (synthesized) |
| Source | 300W (profiled) |
| Pose range | ±90° yaw |
| Evaluation | AFLW2000 |
| Used by | All HeadPose models |
!!! info "Download & Reference"
**Paper**: [Face Alignment Across Large Poses: A 3D Solution](https://arxiv.org/abs/1511.07212)
**Training code**: [yakhyo/head-pose-estimation](https://github.com/yakhyo/head-pose-estimation)
!!! note "UniFace Models"
All HeadPose models shipped with UniFace are trained on 300W-LP and evaluated on AFLW2000.
---
### Face Parsing
#### CelebAMask-HQ
High-quality face parsing dataset with pixel-level annotations for 19 facial component classes.
| Property | Value |
| ---------- | ---------------------------- |
| Images | 30,000 |
| Classes | 19 facial components |
| Resolution | High quality |
| Used by | BiSeNet (ResNet18, ResNet34) |
!!! info "Source"
**GitHub**: [switchablenorms/CelebAMask-HQ](https://github.com/switchablenorms/CelebAMask-HQ)
**Training code**: [yakhyo/face-parsing](https://github.com/yakhyo/face-parsing)
**Dataset structure:**
```
dataset/
├── images/ # Input face images
│ ├── image1.jpg
│ └── ...
└── labels/ # Segmentation masks
├── image1.png
└── ...
```
---
### Attribute Analysis
#### CelebA
Large-scale face attributes dataset widely used for training age and gender prediction models.
| Property | Value |
| ---------- | -------------------- |
| Images | ~200K |
| Attributes | 40 binary attributes |
| Used by | AgeGender |
!!! info "Reference"
**Paper**: [Deep Learning Face Attributes in the Wild](https://arxiv.org/abs/1411.7766)
---
#### FairFace
Face attribute dataset designed for balanced representation across race, gender, and age groups. Provides more equitable predictions compared to imbalanced datasets.
| Property | Value |
| ---------- | ----------------------------------- |
| Attributes | Race (7), Gender (2), Age Group (9) |
| Used by | FairFace |
| License | CC BY 4.0 |
!!! info "Reference"
**Paper**: [FairFace: Face Attribute Dataset for Balanced Race, Gender, and Age](https://arxiv.org/abs/1908.04913)
**ONNX inference**: [yakhyo/fairface-onnx](https://github.com/yakhyo/fairface-onnx)
---
#### AffectNet
Large-scale facial expression dataset for emotion recognition training.
| Property | Value |
| -------- | ----------------------------------------------------------------------- |
| Classes | 7 or 8 (Neutral, Happy, Sad, Surprise, Fear, Disgust, Angry + Contempt) |
| Used by | Emotion (AFFECNET7, AFFECNET8) |
!!! info "Reference"
**Paper**: [AffectNet: A Database for Facial Expression, Valence, and Arousal Computing in the Wild](https://ieeexplore.ieee.org/document/8013713)
---
## Evaluation Benchmarks
### Face Detection
#### WIDER FACE Validation Set
The standard benchmark for face detection models. Results are reported across three difficulty subsets.
| Subset | Criteria |
| ------ | --------------------------------------------- |
| Easy | Large, clear, unoccluded faces |
| Medium | Moderate scale and occlusion |
| Hard | Small, heavily occluded, or challenging faces |
See [Model Zoo - Detection](models.md#face-detection-models) for per-model accuracy on each subset.
---
### Face Recognition
Recognition models are evaluated across multiple benchmarks. Aligned 112x112 validation datasets are available as a single download.
!!! info "Download"
**Kaggle**: [agedb-30-calfw-cplfw-lfw-aligned-112x112](https://www.kaggle.com/datasets/yakhyokhuja/agedb-30-calfw-cplfw-lfw-aligned-112x112)
| Benchmark | Description | Used by |
| ------------ | ----------------------------------------------------------------- | ------------------------------- |
| **LFW** | Labeled Faces in the Wild - standard face verification benchmark | ArcFace, MobileFace, SphereFace |
| **CALFW** | Cross-Age LFW - face verification across age gaps | MobileFace, SphereFace |
| **CPLFW** | Cross-Pose LFW - face verification across pose variations | MobileFace, SphereFace |
| **AgeDB-30** | Age database with 30-year age gaps | ArcFace, MobileFace, SphereFace |
| **CFP-FP** | Celebrities in Frontal-Profile - frontal vs. profile verification | ArcFace |
| **IJB-B** | IARPA Janus Benchmark B - TAR@FAR=0.01% | AdaFace |
| **IJB-C** | IARPA Janus Benchmark C - TAR@FAR=1e-4 | AdaFace, ArcFace |
See [Model Zoo - Recognition](models.md#face-recognition-models) for per-model accuracy on each benchmark.
---
### Gaze Estimation
| Benchmark | Metric | Description |
| -------------------- | ------------- | -------------------------------------------- |
| **Gaze360 test set** | MAE (degrees) | Mean Absolute Error in gaze angle prediction |
See [Model Zoo - Gaze](models.md#gaze-estimation-models) for per-model MAE scores.
---
## Training Repositories
For training your own models or reproducing results, see the following repositories:
| Task | Repository | Datasets Supported |
| ----------- | ------------------------------------------------------------------------- | ------------------------------- |
| Detection | [yakhyo/retinaface-pytorch](https://github.com/yakhyo/retinaface-pytorch) | WIDER FACE |
| Recognition | [yakhyo/face-recognition](https://github.com/yakhyo/face-recognition) | MS1MV2, CASIA-WebFace, VGGFace2 |
| Gaze | [yakhyo/gaze-estimation](https://github.com/yakhyo/gaze-estimation) | Gaze360, MPIIFaceGaze |
| Parsing | [yakhyo/face-parsing](https://github.com/yakhyo/face-parsing) | CelebAMask-HQ |
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