A Multi-World Approach To Question Answering About Real-World Scenes Based On Uncertain Input
ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 27 (NIPS 2014)(2014)
摘要
We propose a method for automatically answering questions about images by bringing together recent advances from natural language processing and computer vision. We combine discrete reasoning with uncertain predictions by a multi-world approach that represents uncertainty about the perceived world in a bayesian framework. Our approach can handle human questions of high complexity about realistic scenes and replies with range of answer like counts, object classes, instances and lists of them. The system is directly trained from question-answer pairs. We establish a first benchmark for this task that can be seen as a modern attempt at a visual turing test.
更多查看译文
关键词
artificial intelligence,computer science
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要