Towards Understanding Cross Resolution Feature Matching for Surveillance Face Recognition

Keyphrases

• Benchmark Dataset 20%
• Clear Margins 20%
• Cross-age Face Recognition 100%
• Cross-resolution 100%
• Domain Gap 20%
• Downscaling 20%
• Face Recognition 40%
• Feature Matching 100%
• Feature Space 20%
• High-resolution 100%
• High-resolution Network 20%
• Human Perception 20%
• Human-machine Systems 20%
• Identity Preserving 40%
• Input Resolution 20%
• Low Contrast 20%
• Low Resolution Faces 20%
• Machine Recognition 20%
• Multi-fold 20%
• Performance Drop 20%
• Performance Gain 20%
• Performance Gap 20%
• Pose Variation 20%
• Real-world Degradation 20%
• Resolution Changes 20%
• SCface 20%
• Super-resolution 20%
• Surveillance Camera 20%
• Surveillance Face Recognition 100%
• Surveillance Scenarios 20%
• Texture Variation 20%
• Upsampling 20%
• Watch List 20%

Computer Science

• Artificial Intelligence 12%
• Face Recognition 100%
• Feature Space 12%
• Human Perception 12%
• Low Resolution Image 12%
• Performance Gain 12%
• Performance Gap 12%
• Pose Variation 12%
• super resolution 25%
• Surveillance Camera 12%

Biochemistry, Genetics and Molecular Biology

• Artificial Intelligence 12%
• Cross-Matching 12%
• Facial Recognition 100%
• Solution and Solubility 12%