A Comprehensive Investigation on Image Caption Generation using Deep Neural Networks - Naik, Haraprasad; Tripathy, Saswati; Laxmi Priya; Sahu, Prajna Paramita (INFOCOMP Journal of Computer Science, 2022)
Caption Generation from an Image is a task that has close relationship with Object Detection and Natural Language Processing. However, The Object Detection has been evolving tremendously since a decade. In the Traditional approach of Object Detection there is an involvement of three step process, which includes (1) region selection (2) Feature Extraction and (3) Classification. But in current days research trends Neural Networks are used to overcome the hand-crafted feature extraction along with the application of classification algorithm through various algorithm such as SVM, AdaBoost and Deformable Part Model (DPM). Similarly, to generate a Caption we can take the help of Neural Network specifically Recurrent Neural Network (RNN). In most of the Caption Generator a variation of RNN is used, that is Long Short-Term Memory (LSTM). Many researchers adopts either sampling or Beam Search to generate a valid sentence/caption. In this paper our aim is to capture the fundamental idea behind the presently available Image Caption Generator and compare their architectural design with their performance.