Spatio-Temporal Transformer Network: Can Text Detection Be Achieved Through It?

In computer vision, visual object tracking is a crucial yet difficult research problem. Object tracking has made significant progress in recent years using convolutional neural networks. Recently, NEC Laboratories, Palo Alto Research Center, Amazon, PARC, and Stanford University academics collaborated to solve the problem of realistically modifying scene text in videos. As a result of the foregoing research approach, the researchers termed their framework STRIVE (Scene Text Replacement In VidEos). The main objective of this research is to develop custom content for marketing and promotional objectives.  Several attempts have been made to automate text replacement in still photos using deep style transfer concepts. Training an image-based text style transfer module on individual fra