insightface/recognition/partial_fc/pytorch

Parital FC

TODO

• No BUG Sampling
• Pytorch Experiments (Glint360k, 1.0/0.1)
• Mixed precision training
• Pipeline Parallel
• Checkpoint
• Docker
• A Wonderful Documents

How to run

cuda=10.1
pytorch==1.6.0
pip install -r requirement.txt

bash run.sh

使用 bash run.sh 这个命令运行。

Results

There is a loss of accuracy in MS1MV2 with sampling, but it has the same good accuracy in Glint360k.

IJBC-Glint360K (mxnet)

+--------------+-------+-------+--------+-------+-------+-------+
|   Methods    | 1e-06 | 1e-05 | 0.0001 | 0.001 |  0.01 |  0.1  |
+--------------+-------+-------+--------+-------+-------+-------+
| IJBC-1.0     | 91.29 | 95.92 | 97.30  | 98.13 | 98.78 | 99.28 |
+--------------+-------+-------+--------+-------+-------+-------+
| IJBC-0.1     | 91.25 | 95.89 | 97.27  | 98.12 | 98.77 | 99.28 |
+--------------+-------+-------+--------+-------+-------+-------+

IJBC-Glint360K (pytorch)

+--------------+-------+-------+--------+-------+-------+-------+
|   Methods    | 1e-06 | 1e-05 | 0.0001 | 0.001 |  0.01 |  0.1  |
+--------------+-------+-------+--------+-------+-------+-------+
| IJBC-1.0     |       |       |        |       |       |       |
+--------------+-------+-------+--------+-------+-------+-------+
| IJBC-0.1     |       |       |        |       |       |       |
+--------------+-------+-------+--------+-------+-------+-------+

IJBC-MS1MV2 (pytorch)

+--------------+-------+-------+--------+-------+-------+-------+
|   Methods    | 1e-06 | 1e-05 | 0.0001 | 0.001 |  0.01 |  0.1  |
+--------------+-------+-------+--------+-------+-------+-------+
| IJBC-1.0     | 86.63 | 94.22 | 96.27  | 97.61 | 98.34 | 99.08 |
+--------------+-------+-------+--------+-------+-------+-------+
| IJBC-0.1     | 76.76 | 92.34 | 96.24  | 97.61 | 98.51 | 99.16 |
+--------------+-------+-------+--------+-------+-------+-------+

Citation

If you find Partial-FC or Glint360K useful in your research, please consider to cite the following related paper:

Partial FC

@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}
}