Predict Pedestrian Trajectories

Project to modify the code of the paper “Social LSTM: Human Trajectory Prediction in Crowded Spaces” to improve accuracy, which was written in Python with Tensorflow. The core idea of the paper was to predict the trajectories of pedestrians using LSTM neural networks. Project for the course of Multimedia Communication at the University of Trento.