Face Transformer for Recognition

Overview

Face-Transformer

This is the code of Face Transformer for Recognition (https://arxiv.org/abs/2103.14803v2).

Recently there has been great interests of Transformer not only in NLP but also in computer vision. We wonder if transformer can be used in face recognition and whether it is better than CNNs. Therefore, we investigate the performance of Transformer models in face recognition. The models are trained on a large scale face recognition database MS-Celeb-1M and evaluated on several mainstream benchmarks, including LFW, SLLFW, CALFW, CPLFW, TALFW, CFP-FP, AGEDB and IJB-C databases. We demonstrate that Transformer models achieve comparable performance as CNN with similar number of parameters and MACs.

arch

Usage Instructions

1. Preparation

The code is mainly adopted from Vision Transformer, and DeiT. In addition to PyTorch and torchvision, install vit_pytorch by Phil Wang, and package timm==0.3.2 by Ross Wightman. Sincerely appreciate for their contributions.

pip install vit-pytorch
pip install timm==0.3.2

Copy the files of fold "copy-to-vit_pytorch-path" to vit-pytorch path.

.
├── __init__.py
├── vit_face.py
└── vits_face.py

2. Databases

You can download the training databases, MS-Celeb-1M (version ms1m-retinaface), and put it in folder 'Data'.

You can download the testing databases as follows and put them in folder 'eval'.

3. Train Models

  • ViT-P8S8
CUDA_VISIBLE_DEVICES='0,1,2,3' python3 -u train.py -b 480 -w 0,1,2,3 -d retina -n VIT -head CosFace --outdir ./results/ViT-P8S8_ms1m_cosface_s1 --warmup-epochs 1 --lr 3e-4 

CUDA_VISIBLE_DEVICES='0,1,2,3' python3 -u train.py -b 480 -w 0,1,2,3 -d retina -n VIT -head CosFace --outdir ./results/ViT-P8S8_ms1m_cosface_s2 --warmup-epochs 0 --lr 1e-4 -r path_to_model 

CUDA_VISIBLE_DEVICES='0,1,2,3' python3 -u train.py -b 480 -w 0,1,2,3 -d retina -n VIT -head CosFace --outdir ./results/ViT-P8S8_ms1m_cosface_s3 --warmup-epochs 0 --lr 5e-5 -r path_to_model 
  • ViT-P12S8
CUDA_VISIBLE_DEVICES='0,1,2,3' python3 -u train.py -b 480 -w 0,1,2,3 -d retina -n VITs -head CosFace --outdir ./results/ViT-P12S8_ms1m_cosface_s1 --warmup-epochs 1 --lr 3e-4 

CUDA_VISIBLE_DEVICES='0,1,2,3' python3 -u train.py -b 480 -w 0,1,2,3 -d retina -n VITs -head CosFace --outdir ./results/ViT-P12S8_ms1m_cosface_s2 --warmup-epochs 0 --lr 1e-4 -r path_to_model 

CUDA_VISIBLE_DEVICES='0,1,2,3' python3 -u train.py -b 480 -w 0,1,2,3 -d retina -n VITs -head CosFace --outdir ./results/ViT-P12S8_ms1m_cosface_s3 --warmup-epochs 0 --lr 5e-5 -r path_to_model 

4. Pretrained Models and Test Models (on LFW, SLLFW, CALFW, CPLFW, TALFW, CFP_FP, AGEDB)

You can download the following models

You can test Models

python test.py --model ./results/ViT-P12S8_ms1m_cosface/Backbone_VITs_Epoch_2_Batch_12000_Time_2021-03-17-04-05_checkpoint.pth --network VIT 

python test.py --model ./results/ViT-P12S8_ms1m_cosface/Backbone_VITs_Epoch_2_Batch_12000_Time_2021-03-17-04-05_checkpoint.pth --network VITs 
Owner
Zhong Yaoyao
BUPT
Zhong Yaoyao
ICCV2021 Paper: AutoShape: Real-Time Shape-Aware Monocular 3D Object Detection

ICCV2021 Paper: AutoShape: Real-Time Shape-Aware Monocular 3D Object Detection

Zongdai 107 Dec 20, 2022
A flexible ML framework built to simplify medical image reconstruction and analysis experimentation.

meddlr Getting Started Meddlr is a config-driven ML framework built to simplify medical image reconstruction and analysis problems. Installation To av

Arjun Desai 36 Dec 16, 2022
Convert BART models to ONNX with quantization. 3X reduction in size, and upto 3X boost in inference speed

fast-Bart Reduction of BART model size by 3X, and boost in inference speed up to 3X BART implementation of the fastT5 library (https://github.com/Ki6a

Siddharth Sharma 19 Dec 09, 2022
Constraint-based geometry sketcher for blender

Constraint-based sketcher addon for Blender that allows to create precise 2d shapes by defining a set of geometric constraints like tangent, distance,

1.7k Dec 31, 2022
Contains a bunch of different python programm tasks

py_tasks Contains a bunch of different python programm tasks Armstrong.py - calculate Armsrong numbers in range from 0 to n with / without cache and c

Dmitry Chmerenko 1 Dec 17, 2021
It is a system used to detect bone fractures. using techniques deep learning and image processing

MohammedHussiengadalla-Intelligent-Classification-System-for-Bone-Fractures It is a system used to detect bone fractures. using techniques deep learni

Mohammed Hussien 7 Nov 11, 2022
Few-shot Learning of GPT-3

Few-shot Learning With Language Models This is a codebase to perform few-shot "in-context" learning using language models similar to the GPT-3 paper.

Tony Z. Zhao 224 Dec 28, 2022
Nvidia Semantic Segmentation monorepo

Paper | YouTube | Cityscapes Score Pytorch implementation of our paper Hierarchical Multi-Scale Attention for Semantic Segmentation. Please refer to t

NVIDIA Corporation 1.6k Jan 04, 2023
Cascaded Pyramid Network (CPN) based on Keras (Tensorflow backend)

ML2 Takehome Project Reimplementing the paper: Cascaded Pyramid Network for Multi-Person Pose Estimation Dataset The model uses the COCO dataset which

Vo Van Tu 1 Nov 22, 2021
A Peer-to-peer Platform for Secure, Privacy-preserving, Decentralized Data Science

PyGrid is a peer-to-peer network of data owners and data scientists who can collectively train AI models using PySyft. PyGrid is also the central serv

OpenMined 615 Jan 03, 2023
Official Pytorch Implementation of Length-Adaptive Transformer (ACL 2021)

Length-Adaptive Transformer This is the official Pytorch implementation of Length-Adaptive Transformer. For detailed information about the method, ple

Clova AI Research 93 Dec 28, 2022
Automatic detection and classification of Covid severity degree in LUS (lung ultrasound) scans

Final-Project Final project in the Technion, Biomedical faculty, by Mor Ventura, Dekel Brav & Omri Magen. Subproject 1: Automatic Detection of LUS Cha

Mor Ventura 1 Dec 18, 2021
GitHub repository for "Improving Video Generation for Multi-functional Applications"

Improving Video Generation for Multi-functional Applications GitHub repository for "Improving Video Generation for Multi-functional Applications" Pape

Bernhard Kratzwald 328 Dec 07, 2022
Public repo for the ICCV2021-CVAMD paper "Is it Time to Replace CNNs with Transformers for Medical Images?"

Is it Time to Replace CNNs with Transformers for Medical Images? Accepted at ICCV-2021: Workshop on Computer Vision for Automated Medical Diagnosis (C

Christos Matsoukas 80 Dec 27, 2022
HashNeRF-pytorch - Pure PyTorch Implementation of NVIDIA paper on Instant Training of Neural Graphics primitives

HashNeRF-pytorch Instant-NGP recently introduced a Multi-resolution Hash Encodin

Yash Sanjay Bhalgat 616 Jan 06, 2023
Code for the Shortformer model, from the paper by Ofir Press, Noah A. Smith and Mike Lewis.

Shortformer This repository contains the code and the final checkpoint of the Shortformer model. This file explains how to run our experiments on the

Ofir Press 138 Apr 15, 2022
The end-to-end platform for building voice products at scale

Picovoice Made in Vancouver, Canada by Picovoice Picovoice is the end-to-end platform for building voice products on your terms. Unlike Alexa and Goog

Picovoice 318 Jan 07, 2023
Rotary Transformer

[中文|English] Rotary Transformer Rotary Transformer is an MLM pre-trained language model with rotary position embedding (RoPE). The RoPE is a relative

325 Jan 03, 2023
Hyperopt for solving CIFAR-100 with a convolutional neural network (CNN) built with Keras and TensorFlow, GPU backend

Hyperopt for solving CIFAR-100 with a convolutional neural network (CNN) built with Keras and TensorFlow, GPU backend This project acts as both a tuto

Guillaume Chevalier 103 Jul 22, 2022
A MNIST-like fashion product database. Benchmark

Fashion-MNIST Table of Contents Why we made Fashion-MNIST Get the Data Usage Benchmark Visualization Contributing Contact Citing Fashion-MNIST License

Zalando Research 10.5k Jan 08, 2023