History

liaoxingyu 7e652fea2a feat: Add contiguous parameters support Support contiguous parameters to train faster. It can split parameters into different contiguous groups by freeze_layer, lr and weight decay.		2021-07-05 11:10:37 +08:00
..
configs	Support amp and resume training in fastface	2021-05-31 17:30:43 +08:00
fastface	feat: Add contiguous parameters support	2021-07-05 11:10:37 +08:00
README.md	update fastreid v1.2	2021-04-02 21:33:13 +08:00
train_net.py	Support amp and resume training in fastface	2021-05-31 17:30:43 +08:00

README.md

FastFace in FastReID

This project provides a baseline for face recognition.

Datasets Preparation

Function	Dataset
Train	MS-Celeb-1M
Test-1	LFW
Test-2	CPLFW
Test-3	CALFW
Test-4	VGG2_FP
Test-5	AgeDB-30
Test-6	CFP_FF
Test-7	CFP-FP

We do data wrangling following InsightFace_Pytorch instruction.

Dependencies

bcolz
mxnet (optional) if you want to read .rec directly

Experiment Results

We refer to insightface_pytorch as our baseline methods, and on top of it, we use circle loss and cosine lr scheduler.

Method	LFW(%)	CFP-FF(%)	CFP-FP(%)	AgeDB-30(%)	calfw(%)	cplfw(%)	vgg2_fp(%)
insightface_pytorch	99.52	99.62	95.04	96.22	95.57	91.07	93.86
ir50_se	99.70	99.60	96.43	97.87	95.95	91.10	94.32
ir100_se	99.65	99.69	97.10	97.98	96.00	91.53	94.62
ir50_se_0.1
ir100_se_0.1