No-Reference Video Quality Assessment Using Transformers and Attention Recurrent Networks

Keyphrases

• Assessment Approach 50%
• Competitive Results 50%
• Complex Distortion 50%
• Corrupted Images 50%
• Distortion Type 50%
• High Performance 50%
• Human Action Recognition 50%
• Learning Task 50%
• Masked Autoencoder 50%
• Memory Block 50%
• Multiple Frames 50%
• No-reference Video Quality Assessment 100%
• Popular 50%
• Recurrent Network 100%
• Recurrent Neural Network 50%
• Self-supervised Learning 50%
• Shifted Window 100%
• Spatial Distortion 100%
• Spatio-temporal Features 100%
• Spatiotemporal Sequence 50%
• Specific Types 50%
• SROCC 50%
• State-of-the-art Models 50%
• Temporal Memory 50%
• Transfer Learning 50%
• Transfer Learning Model 50%
• Transformer 100%
• Transformer Architecture 50%
• Transformer Model 50%
• Video Data 50%
• Video Degradation 50%
• Video Quality 50%
• Video Quality Assessment 100%

Computer Science

• Autoencoder 33%
• Distortion Type 33%
• human action recognition 33%
• Recurrent Network 100%
• Recurrent Neural Network 33%
• Self-Supervised Learning 33%
• Temporal Feature 66%
• Temporal Sequence 33%
• Transfer Learning 66%
• Transformer Model 33%
• Video Quality Assessment 100%