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| author | Jules Laplace <julescarbon@gmail.com> | 2019-01-17 15:11:47 +0100 |
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| committer | Jules Laplace <julescarbon@gmail.com> | 2019-01-17 15:11:47 +0100 |
| commit | 85ae432fb6c6c17292b319bca068e46a4ea81eb3 (patch) | |
| tree | 4d0270fac0fdc7c1c1333af9c4bb82c6eb00669d /notes | |
| parent | c293006ba43944ffeb4dcab17b2256f3a5491a36 (diff) | |
| parent | 03ad11fb2a3dcd425d50167b15d72d4e0ef536a2 (diff) | |
Merge branch 'master' of github.com:adamhrv/megapixels_dev
Diffstat (limited to 'notes')
| -rw-r--r-- | notes/frameworks/face_recognition.md | 31 |
1 files changed, 31 insertions, 0 deletions
diff --git a/notes/frameworks/face_recognition.md b/notes/frameworks/face_recognition.md new file mode 100644 index 00000000..ae359b0d --- /dev/null +++ b/notes/frameworks/face_recognition.md @@ -0,0 +1,31 @@ +# VGG Face 2 Models + +- use the VGG `SE-ResNet-50-256D` .caffemodel +- mean values and size in prototxt +- training used faces detected with MTCNN using 0.3 scale bbox expansion, thresholded at borders +- for megapixels, we are using the opencv dnn face detector which has +- variation for using OpenCV DNN face detector on test set yields + +| Detector | Center | Width | Height | +|:-:|:-:|:-:|:-:| +| OpenCV DNN | 0.0271% | 3.440% | 3.306% | +| MTCNN PyTorch | - | - | - | +| MTCNN TensorFlow | - | - | - | +| MTCNN Caffe | - | - | - | + +### VGG Face 2 TAR@FAR + +- From <https://github.com/ox-vgg/vgg_face2> +- http://www.robots.ox.ac.uk/~vgg/data/vgg_face2/ +- TAR: True Acceptance Rate, FAR: False Acceptance Rate + +| Architecture | Feat dim | Pretrain | TAR@FAR = 0.001 | TAR@FAR = 0.01 | Model Link | +|:-:|:-:|:-:|:-:|:-:|:-:| +| ResNet-50 | 2048 | N | 0.878 | 0.938 | [Caffe](http://www.robots.ox.ac.uk/~vgg/data/vgg_face2/models/caffe/resnet50_scratch_caffe.tar.gz), [MatConvNet](http://www.robots.ox.ac.uk/~vgg/data/vgg_face2/models/matconvnet/resnet50_scratch_mat.tar.gz), [TF], [PyTorch](http://www.robots.ox.ac.uk/~vgg/data/vgg_face2/models/pytorch/resnet50_scratch_pytorch.tar.gz) | +| ResNet-50 | 2048 | Y | 0.891 | 0.947 | [Caffe](http://www.robots.ox.ac.uk/~vgg/data/vgg_face2/models/caffe/resnet50_ft_caffe.tar.gz), [MatConvNet](http://www.robots.ox.ac.uk/~vgg/data/vgg_face2/models/matconvnet/resnet50_ft_mat.tar.gz), [TF], [PyTorch](http://www.robots.ox.ac.uk/~vgg/data/vgg_face2/models/pytorch/resnet50_ft_pytorch.tar.gz) | +| SE-ResNet-50 | 2048 | N | 0.888 | 0.949 | [Caffe](http://www.robots.ox.ac.uk/~vgg/data/vgg_face2/models/caffe/senet50_scratch_caffe.tar.gz), [MatConvNet](http://www.robots.ox.ac.uk/~vgg/data/vgg_face2/models/matconvnet/senet50_scratch_mat.tar.gz), [TF], [PyTorch](http://www.robots.ox.ac.uk/~vgg/data/vgg_face2/models/pytorch/senet50_scratch_pytorch.tar.gz)| +| SE-ResNet-50 | 2048 | Y | 0.908 | 0.956 | [Caffe](http://www.robots.ox.ac.uk/~vgg/data/vgg_face2/models/caffe/senet50_ft_caffe.tar.gz), [MatConvNet](http://www.robots.ox.ac.uk/~vgg/data/vgg_face2/models/matconvnet/senet50_ft_mat.tar.gz), [TF], [PyTorch](http://www.robots.ox.ac.uk/~vgg/data/vgg_face2/models/pytorch/senet50_ft_pytorch.tar.gz)| +| ResNet-50-256D | 256 | Y | 0.898 | 0.956 | [Caffe](http://www.robots.ox.ac.uk/~vgg/data/vgg_face2/models/caffe/resnet50_256_caffe.tar.gz), [MatConvNet](http://www.robots.ox.ac.uk/~vgg/data/vgg_face2/models/matconvnet/resnet50_256_mat.tar.gz), [TF], [PyTorch](http://www.robots.ox.ac.uk/~vgg/data/vgg_face2/models/pytorch/resnet50_256_pytorch.tar.gz) | +| ResNet-50-128D | 128 | Y | 0.904 | 0.956 | [Caffe](http://www.robots.ox.ac.uk/~vgg/data/vgg_face2/models/caffe/resnet50_128_caffe.tar.gz), [MatConvNet](http://www.robots.ox.ac.uk/~vgg/data/vgg_face2/models/matconvnet/resnet50_128_mat.tar.gz), [TF], [PyTorch](http://www.robots.ox.ac.uk/~vgg/data/vgg_face2/models/pytorch/resnet50_128_pytorch.tar.gz) | +| SE-ResNet-50-256D| 256 | Y | 0.912 | 0.965 | [Caffe](http://www.robots.ox.ac.uk/~vgg/data/vgg_face2/models/caffe/senet50_256_caffe.tar.gz), [MatConvNet](http://www.robots.ox.ac.uk/~vgg/data/vgg_face2/models/matconvnet/senet50_256_mat.tar.gz), [TF], [PyTorch](http://www.robots.ox.ac.uk/~vgg/data/vgg_face2/models/pytorch/senet50_256_pytorch.tar.gz)| +| SE-ResNet-50-128D| 128 | Y | 0.910 | 0.959 | [Caffe](http://www.robots.ox.ac.uk/~vgg/data/vgg_face2/models/caffe/senet50_128_caffe.tar.gz), [MatConvNet](http://www.robots.ox.ac.uk/~vgg/data/vgg_face2/models/matconvnet/senet50_128_mat.tar.gz), [TF], [PyTorch](http://www.robots.ox.ac.uk/~vgg/data/vgg_face2/models/pytorch/senet50_128_pytorch.tar.gz) | |