Qinji Guan

1. Comparator Networks
Presented by Qingji Guan

2. Objective
• Set-base verification
• If two sets of images of a face are of the same person or not
• Sets of faces -> ‘templates’
• Common approach
• Generate a vector representing each face using CNN, and simply average these
these vectors to obtain a vector representation for the entire template
• Problems
• viewpoint conditioned similarity
• Local landmark comparison
• Within template weighting
• Between template weighting

3. Deep Comparator Network

4. Deep Comparator Network
Detect module

5. Deep Comparator Network
Landmark Regularizers
Diversity Regularizer
Keypoints Regularizer

6. Deep Comparator Network

7. Deep Comparator Network

8. Experiment

9. Experiment

10. Experiment