InsightFace: 2D and 3D Face Analysis Project

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InsightFace project is mainly maintained by Jia Guo and Jiankang Deng.

For more information, please visit our website at https://insightface.ai

License

The code of InsightFace is released under the MIT License. There is no limitation for both academic and commercial usage.

The training data containing the annotation (and the models trained with these data) are available for non-commercial research purposes only.

Both manual-downloading models from our github repo and auto-downloading models with our python-library follow the above license policy(which is for non-commercial research purposes only).

2025-11-24 Update:

1. For inswapper series face swap models (e.g., inswapper_128.onnx/inswapper-512-live), please contact contact@insightface.ai for licensing and additional support.
2. For open-sourced face recognition models (e.g., buffalo_l package), please contact recognition-oss-pack@insightface.ai for licensing.
3. For advanced face recognition SDK and models (e.g., InspireFace SDK), please contact contact@insightface.ai for licensing and additional support.

Top News

2025-11-18 [Picsi.ai] Released Live Face Swap macOS & iOS App and updated Picsi.ai services with our latest series of swap models (incl. inswapper-512-live/Cyn/Dax).

2024-05-04 [Picsi.ai] Released InspireFace, a cross-platform C/C++ face recognition SDK.

2022-08-12: We achieved Rank-1st of Perspective Projection Based Monocular 3D Face Reconstruction Challenge of ECCV-2022 WCPA Workshop, paper and code.

2021-10-29: We achieved 1st place on the VISA track of NIST-FRVT 1:1 by using Partial FC (Xiang An, Jiankang Deng, Jia Guo).

ChangeLogs

2025-11-18 [Picsi.ai] Released Live Face Swap macOS & iOS App and updated Picsi.ai services with our latest series of swap models (incl. inswapper-live/Cyn/Dax).

2024-05-04 [Picsi.ai] Released InspireFace, a cross-platform C/C++ face recognition SDK.

2024-04-17: Monocular Identity-Conditioned Facial Reflectance Reconstruction accepted by CVPR-2024.

2023-08-08: We released the implementation of Generalizing Gaze Estimation with Weak-Supervision from Synthetic Views at reconstruction/gaze.

2023-05-03: We have launched the ongoing version of wild face anti-spoofing challenge. See details here.

2023-02-13: We launch a large scale in the wild face anti-spoofing challenge on CVPR23 Workshop, see details at challenges/cvpr23-fas-wild.

2022-11-28: Single line code for facial identity swapping in our python packge ver 0.7, please check the example here.

2022-10-28: MFR-Ongoing website is refactored, please create issues if there's any bug.

2022-09-22: Now we have web-demos: face-localization, face-recognition, and face-swapping.

2022-08-12: We achieved Rank-1st of Perspective Projection Based Monocular 3D Face Reconstruction Challenge of ECCV-2022 WCPA Workshop, paper and code.

2022-03-30: Partial FC accepted by CVPR-2022.

2022-02-23: SCRFD accepted by ICLR-2022.

2021-11-30: MFR-Ongoing challenge launched(same with IFRT), which is an extended version of iccv21-mfr.

2021-10-29: We achieved 1st place on the VISA track of NIST-FRVT 1:1 by using Partial FC (Xiang An, Jiankang Deng, Jia Guo).

2021-10-11: Leaderboard of ICCV21 - Masked Face Recognition Challenge released. Video: Youtube, Bilibili.

2021-06-05: We launch a Masked Face Recognition Challenge & Workshop on ICCV 2021.

Introduction

InsightFace is an open source 2D&3D deep face analysis toolbox, mainly based on PyTorch and MXNet.

Please check our website for detail.

The master branch works with PyTorch 1.6+ and/or MXNet=1.6-1.8, with Python 3.x.

InsightFace efficiently implements a rich variety of state of the art algorithms of face recognition, face detection and face alignment, which optimized for both training and deployment.

Quick Start

Please start with our python-package, for testing detection, recognition and alignment models on input images.

ArcFace Video Demo

<img src=https://raw.githubusercontent.com/nttstar/insightface-resources/refs/heads/master/images/facerecognitionfromvideo.PNG width="760" />

Please click the image to watch the Youtube video. For Bilibili users, click here.

Projects

The page on InsightFace website also describes all supported projects in InsightFace.

You may also interested in some challenges hold by InsightFace.

Face Recognition

Introduction

In this module, we provide training data, network settings and loss designs for deep face recognition.

The supported methods are as follows:

• [x] ArcFace_mxnet (CVPR'2019)
• [x] ArcFace_torch (CVPR'2019)
• [x] SubCenter ArcFace (ECCV'2020)
• [x] PartialFC_mxnet (CVPR'2022)
• [x] PartialFC_torch (CVPR'2022)
• [x] VPL (CVPR'2021)
• [x] Arcface_oneflow
• [x] ArcFace_Paddle (CVPR'2019)

Commonly used network backbones are included in most of the methods, such as IResNet, MobilefaceNet, MobileNet, InceptionResNet_v2, DenseNet, etc..

Datasets

The training data includes, but not limited to the cleaned MS1M, VGG2 and CASIA-Webface datasets, which were already packed in MXNet binary format. Please dataset page for detail.

Evaluation

We provide standard IJB and Megaface evaluation pipelines in evaluation

Pretrained Models

Please check Model-Zoo for more pretrained models.

Third-party Re-implementation of ArcFace

• TensorFlow: InsightFace_TF
• TensorFlow: tf-insightface
• TensorFlow:insightface
• PyTorch: InsightFace_Pytorch
• PyTorch: arcface-pytorch
• Caffe: arcface-caffe
• Caffe: CombinedMargin-caffe
• Tensorflow: InsightFace-tensorflow
• TensorRT: wang-xinyu/tensorrtx
• TensorRT: InsightFace-REST
• ONNXRuntime C++: ArcFace-ONNXRuntime
• ONNXRuntime Go: arcface-go
• MNN: ArcFace-MNN
• TNN: ArcFace-TNN
• NCNN: ArcFace-NCNN

Face Detection

Introduction

<div align="left"> <img src="https://raw.githubusercontent.com/nttstar/insightface-resources/refs/heads/master/images/11513D05.jpg" width="640"/> </div>

In this module, we provide training data with annotation, network settings and loss designs for face detection training, evaluation and inference.

The supported methods are as follows:

• [x] RetinaFace (CVPR'2020)
• [x] SCRFD (Arxiv'2021)
• [x] blazeface_paddle

RetinaFace is a practical single-stage face detector whic