mirror of https://github.com/JDAI-CV/fast-reid.git
36 lines
1.2 KiB
Markdown
36 lines
1.2 KiB
Markdown
# FastFace in FastReID
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This project provides a baseline for face recognition.
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## Datasets Preparation
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| Function | Dataset |
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| --- | --- |
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| Train | MS-Celeb-1M |
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| Test-1 | LFW |
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| Test-2 | CPLFW |
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| Test-3 | CALFW |
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| Test-4 | VGG2_FP |
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| Test-5 | AgeDB-30 |
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| Test-6 | CFP_FF |
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| Test-7 | CFP-FP |
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We do data wrangling following [InsightFace_Pytorch](https://github.com/TreB1eN/InsightFace_Pytorch) instruction.
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## Dependencies
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- bcolz
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- mxnet (optional) if you want to read `.rec` directly
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## Experiment Results
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We refer to [insightface_pytorch](https://github.com/TreB1eN/InsightFace_Pytorch) as our baseline methods, and on top of it, we use circle loss and cosine lr scheduler.
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| Method | LFW(%) | CFP-FF(%) | CFP-FP(%)| AgeDB-30(%) | calfw(%) | cplfw(%) | vgg2_fp(%) |
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| :---: | :---: | :---: |:---: | :---: | :---: | :---: | :---: |
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| [insightface_pytorch](https://github.com/TreB1eN/InsightFace_Pytorch) | 99.52 | 99.62 | 95.04 | 96.22 | 95.57 | 91.07 | 93.86 |
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| ir50_se | 99.70 | 99.60 | 96.43 | 97.87 | 95.95 | 91.10 | 94.32 |
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| ir100_se | 99.65 | 99.69 | 97.10 | 97.98 | 96.00 | 91.53 | 94.62 |
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| ir50_se_0.1 | | | | | | | |
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| ir100_se_0.1 | | | | | | | |
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