Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Understanding human actions is a key problem in computer vision. Hover, recognizing actions is only the first step of understanding what a person is doing. ,  introduce the problem of predicting why a person has performed an action in images. This problem has many applications in human activity understanding, such as anticipating or explaining an action. To study this problem,  introduce a new dataset of people performing actions annotated with likely motivations. Hover, the information in an image alone may not be sufficient to automatically solve this task. Since humans can rely on their lifetime of experiences to infer motivation,  propose to give computer vision systems access to some of these experiences by using recently developed natural language models to mine knowledge stored in massive amounts of text. While  are still far away from fully understanding motivation, our results suggest that transferring knowledge from language into vision can help machines understand why people in images might be performing an action.
['Carl Vondrick', 'Deniz Oktay', 'Hamed Pirsiavash', 'Antonio Torralba']
I am writing a research paper on a idea Predicting Motivations of Actions by Leveraging Text
[{"from": "human", "value": "I am writing a research paper on a idea Predicting Motivations of Actions by Leveraging Text"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Understanding human actions is a key problem in computer vision. Hover, recognizing actions is only the first step of understanding what a person is doing. ,  introduce the problem of predicting why a person has performed an action in images. This problem has many applications in human activity understanding, such as anticipating or explaining an action. To study this problem,  introduce a new dataset of people performing actions annotated with likely motivations. Hover, the information in an image alone may not be sufficient to automatically solve this task. Since humans can rely on their lifetime of experiences to infer motivation,  propose to give computer vision systems access to some of these experiences by using recently developed natural language models to mine knowledge stored in massive amounts of text. While  are still far away from fully understanding motivation, our results suggest that transferring knowledge from language into vision can help machines understand why people in images might be performing an action."}]