Learning Deep Features for Discriminative Localization

• Global Average Pooling (GAP) Class Activation Mapping (CAM)

• Bounding box (localization)

•

Convolution layer activation

conv5

input image

https://leonardoaraujosantos.gitbooks.io/artificial-inteligence/content/object_localization_and_detection.html

conv5

input image

https://leonardoaraujosantos.gitbooks.io/artificial-inteligence/content/object_localization_and_detection.html

Unit

Unit

Activation

Global Average Pooling (GAP)

softmax Unit

Activation

Unit

Class Activation Map

Class Activation Map

Class Activation Map

• FC

• AlexNet, VGGnet, GoogLeNet

• GAP Unit Conv

• AlexNet: conv5 13x13

• VGGnet: conv5-3 14x14

• GoogLeNet: inception4e 14x14

• convolution GAP Softmax

• size: 3x3, stride: 1, padding: 1, unit: 1024

• ILSVRC 1000 130 fine tuning

• fine tune

Classification

Localization

20% BOX

Grand Truth

GAP CNN

• GAP SVM

•

•

•

•

• Visual Question Answering

• •

• Hard-negative mining algorithm

• positive set:

• negative set:

• positive set: Google StreetView 350

• negative set:

Visual Question Answering

Class-Specific Units

• GAP Softmax Unit

• CNN bag of words

• Global Average Pooling (GAP) Class Activation Mapping (CAM)

• Bounding box (localization)

•

• FC

• Localization

• GAP CNN