Interactive Attention AI to translate low light photos to captions for night scene understanding in women safety
There is amazing progress in Deep Learning based models for Image captioning and Low Light image enhancement. For the first time in literature, this paper develops a Deep Learning model that translates night scenes to sentences, opening new possibilities for AI applications in the safety of visually impaired women. Inspired by Image Captioning and Visual Question Answering, a novel Interactive Image Captioning is developed. A user can make the AI focus on any chosen person of interest by influencing the attention scoring. Attention context vectors are computed from CNN feature vectors and user-provided start word. The Encoder-Attention-Decoder neural network learns to produce captions from low brightness images. This paper demonstrates how women safety can be enabled by researching a novel AI capability in the Interactive Vision-Language model for perception of the environment in the night.
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Tasks
DecoderDeep LearningImage CaptioningImage EnhancementLanguage ModelingLanguage ModellingLow-Light Image EnhancementQuestion AnsweringScene UnderstandingVisual Question AnsweringVisual Question Answering (VQA)Similar Papers 제목 키워드 기반
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