GQA: Visual Reasoning in the Real World

• GQA dataset
• GQA paper
• GQA CVPR Workshop

Data structure

├── Question Number
    ├── Annotations
    |   ├── answer
    |   ├── full Answer
    |   └── question
    │   
    ├── answer
    ├── entailed
    ├── equivalent
    ├── fullAnswer
    ├── groups
    ├── imageId
    ├── isBalanced
    ├── question
    ├── semantic
    ├── semanticStr
    └── types
        ├── detailed
        ├── semantic
        └── structural

• answer
• imageId
• question

Network Architecture

Image-Question Aggregator

• Image Pretrained
  • Tensornets github
• Question Pretrained
  • ELMo using tensorflow-hub
• Attention model, We just use attention module
  • Self-Attention Generative Adversarial Networks paper
  • Attention github

Requirements

• tensorflow-gpu==1.13.1
• numpy==1.16.2
• tensorflow-hub==0.4.0
• python==3.7.3
• cv2==4.0.0
• tqdm==4.31.1