Comments (3)
There is something wrong about the label, but it doesn't influence the evaluation of the LFW 6,000 pairs because the label are not used in the evaluations nor to create the positive and negative pairs. You can compare the created pairs with the official 6,000 pairs by names.
from face_verification_experiment.
For the first positive pair (57, 60), it seems that the 57th image is 'Abel_Pacheco_0002.jpg', and the 60th image is 'Abid_Hamid_Mahmud_Al-Tikriti_0001.jpg'. They are not the same person. Could you share me your image list when you extract your features? Thanks!
from face_verification_experiment.
The mat file of features has already contained the image list of lfw.
from face_verification_experiment.
Related Issues (20)
- Where do you get the 5 facial points for MSCELEB dataset. Do you use some other model to find the facial points ? HOT 1
- Xavier vs Gaussian HOT 1
- I feel the size of the trainning data doubt HOT 1
- no an issue but a doubt HOT 2
- about lfw labels in model C-LightenedCNN_C_lfw.mat HOT 3
- Error occurred when computing accuracy
- Query
- no such file in your clean list
- Eltwise层名字拼写错误有影响吗?
- MegaFace Evaluation: it generated 'OpenCV Error' when running experiment.py with own features HOT 1
- hello,your model A and B is small,why your model C is bigger than B by using the same cnn architecture HOT 1
- can't get the same result HOT 3
- How to use fine tuned model to do classification for an image in light CNN?
- Any architecture patent information HOT 1
- the issue about architecture
- LightenedCNN_A_deploy.prototxt
- The evaluation of CASIA-NIR2.0
- Request Pretrained lightenedCNN model in .mat format HOT 1
- Computation of rank 1
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from face_verification_experiment.