Official repository for MixFaceNets: Extremely Efficient Face Recognition Networks

Overview

MixFaceNets

This is the official repository of the paper: MixFaceNets: Extremely Efficient Face Recognition Networks.

(Accepted in IJCB2021) https://ieeexplore.ieee.org/abstract/document/9484374

Paper Arxiv

Model MFLOPs Params (M) LFW% AgeDB-30% IJB-B( TAR at FAR1e–6) IJB-C( TAR at FAR1e–6) Pretrained model
MixFaceNet-M 626.1 3.95 99.68 97.05 91.55 93.42 pretrained-mode
ShuffleMixFaceNet-M 626.1 3.95 99.60 96.98 91.47 93.5 pretrained-mode
MixFaceNet-S 451.7 3.07 99.60 96.63 90.17 92.30 pretrained-mode
ShuffleMixFaceNet-S 451.7 3.07 99.58 97.05 90.94 93.08 pretrained-mode
MixFaceNet-XS 161.9 1.04 99.60 95.85 88.48 90.73 pretrained-mode
ShuffleMixFaceNet-XS 161.9 1.04 99.53 95.62 87.86 90.43 pretrained-mode

FLOPs vs. performance on LFW (accuracy), AgeDB-30 (accuracy), MegaFace (TAR at FAR1e-6), IJB-B (TAR at FAR1e-4), IJB-C (TAR at FAR1e-4) and refined version of MegaFace, noted as MegaFace (R), (TAR at FAR1e-6). Our MixFaceNet models are highlighted with triangle marker and red edge color.

LFW LFW

AgeDb-30 LFW

MegaFace LFW

MegaFace(R) LFW

IJB-B LFW

IJB-C LFW

If you find MixFaceNets useful in your research, please cite the following paper:

Citation

@INPROCEEDINGS{9484374,
  author={Boutros, Fadi and Damer, Naser and Fang, Meiling and Kirchbuchner, Florian and Kuijper, Arjan},
  booktitle={2021 IEEE International Joint Conference on Biometrics (IJCB)}, 
  title={MixFaceNets: Extremely Efficient Face Recognition Networks}, 
  year={2021},
  volume={},
  number={},
  pages={1-8},
  doi={10.1109/IJCB52358.2021.9484374}}


The model is trained with ArcFace loss using Partial-FC algorithms. If you train the MixfaceNets with ArcFace and Partial-FC, please follow their distribution licenses.

Citation

@inproceedings{deng2019arcface,
  title={Arcface: Additive angular margin loss for deep face recognition},
  author={Deng, Jiankang and Guo, Jia and Xue, Niannan and Zafeiriou, Stefanos},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
  pages={4690--4699},
  year={2019}
}
@inproceedings{an2020partical_fc,
  title={Partial FC: Training 10 Million Identities on a Single Machine},
  author={An, Xiang and Zhu, Xuhan and Xiao, Yang and Wu, Lan and Zhang, Ming and Gao, Yuan and Qin, Bin and
  Zhang, Debing and Fu Ying},
  booktitle={Arxiv 2010.05222},
  year={2020}
}
Owner
Fadi Boutros
Fadi Boutros
Sequence lineage information extracted from RKI sequence data repo

Pango lineage information for German SARS-CoV-2 sequences This repository contains a join of the metadata and pango lineage tables of all German SARS-

Cornelius Roemer 24 Oct 26, 2022
Benchmark for Answering Existential First Order Queries with Single Free Variable

EFO-1-QA Benchmark for First Order Query Estimation on Knowledge Graphs This repository contains an entire pipeline for the EFO-1-QA benchmark. EFO-1

HKUST-KnowComp 14 Oct 24, 2022
Paaster is a secure by default end-to-end encrypted pastebin built with the objective of simplicity.

Follow the development of our desktop client here Paaster Paaster is a secure by default end-to-end encrypted pastebin built with the objective of sim

Ward 211 Dec 25, 2022
PointPillars inference with TensorRT

A project demonstrating how to use CUDA-PointPillars to deal with cloud points data from lidar.

NVIDIA AI IOT 315 Dec 31, 2022
This is the official repository of the paper Stocastic bandits with groups of similar arms (NeurIPS 2021). It contains the code that was used to compute the figures and experiments of the paper.

Experiments How to reproduce experimental results of Stochastic bandits with groups of similar arms submitted paper ? Section 5 of the paper To reprod

Fabien 0 Oct 25, 2021
[2021 MultiMedia] CONQUER: Contextual Query-aware Ranking for Video Corpus Moment Retrieval

CONQUER: Contexutal Query-aware Ranking for Video Corpus Moment Retreival PyTorch implementation of CONQUER: Contexutal Query-aware Ranking for Video

Hou zhijian 23 Dec 26, 2022
Code of paper Interact, Embed, and EnlargE (IEEE): Boosting Modality-specific Representations for Multi-Modal Person Re-identification.

Interact, Embed, and EnlargE (IEEE): Boosting Modality-specific Representations for Multi-Modal Person Re-identification We provide the codes for repr

12 Dec 12, 2022
PiCIE: Unsupervised Semantic Segmentation using Invariance and Equivariance in clustering (CVPR2021)

PiCIE: Unsupervised Semantic Segmentation using Invariance and Equivariance in Clustering Jang Hyun Cho1, Utkarsh Mall2, Kavita Bala2, Bharath Harihar

Jang Hyun Cho 164 Dec 30, 2022
CROSS-LINGUAL ABILITY OF MULTILINGUAL BERT: AN EMPIRICAL STUDY

M-BERT-Study CROSS-LINGUAL ABILITY OF MULTILINGUAL BERT: AN EMPIRICAL STUDY Motivation Multilingual BERT (M-BERT) has shown surprising cross lingual a

CogComp 1 Feb 28, 2022
Project Tugas Besar pertama Pengenalan Komputasi Institut Teknologi Bandung

Vending_Machine_(Mesin_Penjual_Minuman) Project Tugas Besar pertama Pengenalan Komputasi Institut Teknologi Bandung Raw Sketch untuk Essay Ringkasan P

QueenLy 1 Nov 08, 2021
Empower Sequence Labeling with Task-Aware Language Model

LM-LSTM-CRF Check Our New NER Toolkit 🚀 🚀 🚀 Inference: LightNER: inference w. models pre-trained / trained w. any following tools, efficiently. Tra

Liyuan Liu 838 Jan 05, 2023
Tiny-NewsRec: Efficient and Effective PLM-based News Recommendation

Tiny-NewsRec The source codes for our paper "Tiny-NewsRec: Efficient and Effective PLM-based News Recommendation". Requirements PyTorch == 1.6.0 Tensor

Yang Yu 3 Dec 07, 2022
Official Implementation of DE-DETR and DELA-DETR in "Towards Data-Efficient Detection Transformers"

DE-DETRs By Wen Wang, Jing Zhang, Yang Cao, Yongliang Shen, and Dacheng Tao This repository is an official implementation of DE-DETR and DELA-DETR in

Wen Wang 61 Dec 12, 2022
LRBoost is a scikit-learn compatible approach to performing linear residual based stacking/boosting.

LRBoost is a sckit-learn compatible package for linear residual boosting. LRBoost combines a linear estimator and a non-linear estimator to leverage t

Andrew Patton 5 Nov 23, 2022
official Pytorch implementation of ICCV 2021 paper FuseFormer: Fusing Fine-Grained Information in Transformers for Video Inpainting.

FuseFormer: Fusing Fine-Grained Information in Transformers for Video Inpainting By Rui Liu, Hanming Deng, Yangyi Huang, Xiaoyu Shi, Lewei Lu, Wenxiu

77 Dec 27, 2022
Deep Probabilistic Programming Course @ DIKU

Deep Probabilistic Programming Course @ DIKU

52 May 14, 2022
An Implementation of Transformer in Transformer in TensorFlow for image classification, attention inside local patches

Transformer-in-Transformer An Implementation of the Transformer in Transformer paper by Han et al. for image classification, attention inside local pa

Rishit Dagli 40 Jul 25, 2022
Use AI to generate a optimized stock portfolio

Use AI, Modern Portfolio Theory, and Monte Carlo simulation's to generate a optimized stock portfolio that minimizes risk while maximizing returns. Ho

Greg James 30 Dec 22, 2022
Code for reproducing our paper: LMSOC: An Approach for Socially Sensitive Pretraining

LMSOC: An Approach for Socially Sensitive Pretraining Code for reproducing the paper LMSOC: An Approach for Socially Sensitive Pretraining to appear a

Twitter Research 11 Dec 20, 2022
SciFive: a text-text transformer model for biomedical literature

SciFive SciFive provided a Text-Text framework for biomedical language and natural language in NLP. Under the T5's framework and desrbibed in the pape

Long Phan 54 Dec 24, 2022