This branch is the implementation of the paper "A Comprehensive Study for Center Loss".

• Files
• Trained_Model
• Contact

Implement_Details

The overall pipeline is the same as center loss (https://github.com/ydwen/caffe-face).

In this paper, we use CAISA-WebFace, VGG-Face2 For the details of removing overlapping ID, please refer to https://github.com/happynear/FaceDatasets

Preprocessing We use MTCNN (https://github.com/kpzhang93/MTCNN_face_detection_alignment) to detect five facial keypoints and use them to align the faces. For the alignment details, please see https://github.com/ydwen/caffe-face/blob/caffe-face/face_example/extractDeepFeature.m

Training The training details can be found on according prototxt. Note that the batch size we used is 512.

Loss layer

Center Loss & Generalized Center Loss

    layer {
         name: "generalized_center_loss"
         type: "CenterLoss"
         bottom: "fc5"
         bottom: "label"
         top: "center_loss"
         top: "count"
         param {
             lr_mult: 1
             decay_mult: 1
         }
         center_loss_param {
             num_output: 7994
             margin:5 ##radius##
             center_filler {
               type: "xavier"
             }
         }
         loss_weight: 0.01
         loss_weight: 0.0
     }

Advanced Center Loss & Generalized Center Loss

    layer {
         name: "advanced_center_loss"
         type: "SharedCenterLoss"
         bottom: "fc5"
         bottom: "label"
         top: "shared_center_loss"
         top: "count"
         param {
           name:"center"
           lr_mult: 1
           decay_mult: 1
         }
         param {
           lr_mult: 1
           decay_mult: 0
         }
         shared_center_loss_param {
           num_output: 7994
           margin:5 ##radius##
           gamma_shared: True ##share weights##
           center_filler {
             type: "xavier"
           }
           gamma_filler{
             type:"constant"
             value:1
           }
         }
         loss_weight: 0.01
         loss_weight: 0.0
       }

Files

• caffe
  • caffe.proto
  • center_loss_layer.hpp
  • center_loss_layer.cpp
  • center_loss_layer.cu
  • shared_center_loss_layer.hpp
  • shared_center_loss_layer.cpp
  • shared_center_loss_layer.cu
• deploy_prototxt
  • resnet4.prototxt
  • resnet10.prototxt
  • resnet20.prototxt
  • resnet36.prototxt
  • resnet64.prototxt
• exp4_2
  • Parameter sharing
  • Loss Weight
  • Radius
  • Training_set
  • Depth
• exp4_3
  • softmax
  • softmax + contrastive
  • normface
  • coco
  • SphereFace
  • softmax + CL
  • softmax + ACL
  • softmax + ACL-γ
  • coco + ACL-γ
  • sphere + ACL-γ
• exp4_4 & exp4_5 & exp4_6
  • softmax
  • softmax + CL
  • softmax+ ACL-γ
  • softmax + CL (ρ=5)
  • softmax+ ACL-γ (ρ=5)
  • sphere+ ACL-γ (ρ=5)
• training_list
  • link

Trained_Model

• exp4_2
  • link
• exp4_3
  • link
• exp4_4 & exp4_5 & exp4_6
  • link

Contact

• Yandong Wen
• Kaipeng Zhang

License

Copyright (c) Yandong Wen, Kaipeng Zhang All rights reserved. MIT License