Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Visual question ansring is fundamentally compositional in nature—a question like where is the dog? shares substructure with questions like what color is the dog? and where is the cat?  seeks to simultaneously exploit the representational capacity of deep networks and the compositional linguistic structure of questions.  describe a procedure for constructing and learning neural module networks, which compose collections of jointly-trained neural "modules" into deep networks for question ansring. Our approach decomposes questions into their linguistic substructures, and uses these structures to dynamically instantiate modular networks (with reusable components for recognizing dogs, classifying colors, etc.). The resulting compound networks are jointly trained.  evaluate our approach on two challenging datasets for visual question ansring, achieving state-of-the-art results on both the VQA natural image dataset and a new dataset of complex questions about abstract shapes.
['Jacob Andreas', 'Marcus Rohrbach', 'Trevor Darrell', 'Daniel N. Klein']
I am writing a research paper on a idea Neural Module Networks
[{"from": "human", "value": "I am writing a research paper on a idea Neural Module Networks"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Visual question ansring is fundamentally compositional in nature\u2014a question like where is the dog? shares substructure with questions like what color is the dog? and where is the cat?  seeks to simultaneously exploit the representational capacity of deep networks and the compositional linguistic structure of questions.  describe a procedure for constructing and learning neural module networks, which compose collections of jointly-trained neural \"modules\" into deep networks for question ansring. Our approach decomposes questions into their linguistic substructures, and uses these structures to dynamically instantiate modular networks (with reusable components for recognizing dogs, classifying colors, etc.). The resulting compound networks are jointly trained.  evaluate our approach on two challenging datasets for visual question ansring, achieving state-of-the-art results on both the VQA natural image dataset and a new dataset of complex questions about abstract shapes."}]