Text-to-video model

A text-to-video model is a machine learning model which takes a natural language description as input and producing a video or multiples videos from the input.^[1]

Video prediction on making objects realistic in a stable background is performed by using recurrent neural network for a sequence to sequence model with a connector convolutional neural network encoding and decoding each frame pixel by pixel,^[2] creating video using deep learning.^[3] Testing of the data set in conditional generative model for existing information from text can be done by variational autoencoder and generative adversarial network (GAN).