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Interactive Attention AI to translate low light photos to captions for night scene understanding in women safety

2022-01-04 04:21:07
Rajagopal A, Nirmala V, Arun Muthuraj Vedamanickam
arXiv_CV
                   
Abstract

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.

Abstract (translated)

URL

https://arxiv.org/abs/2201.00969

PDF

https://arxiv.org/pdf/2201.00969.pdf

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