Automated testing of image captioning systems
Boxi Yu, Zhiqing Zhong, Xinran Qin, Jiayi Yao, Yuancheng Wang, Pinjia He
Abstract
Image captioning (IC) systems, which automatically generate a text description of the salient objects in an image (real or synthetic), have seen great progress over the past few years due to the development of deep neural networks. IC plays an indispensable role in human society, for example, labeling massive photos for scientific studies and assisting visually-impaired people in perceiving the world. However, even the top-notch IC systems, such as Microsoft Azure Cognitive Services and IBM Image Caption Generator, may return incorrect results, leading to the omission of important objects, deep misunderstanding, and threats to personal safety.
Topics & Concepts
Closed captioningComputer scienceIBMSalientGenerator (circuit theory)Image (mathematics)Artificial intelligenceVisualizationComputer visionHuman–computer interactionPower (physics)PhysicsQuantum mechanicsMaterials scienceNanotechnologyMultimodal Machine Learning ApplicationsAdvanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning