Before revision:  In this article, we present a non-symmetrical bidirectional recurrent neural network architecture called U-RNN as a sequence encoder and evaluate its relevance to replace LSTMs for various forecasting models.
After revision:  In this article, we present a non-symmetrical bidirectional recurrent neural network architecture called U-RNN to encode pedestrian trajectories and evaluate its relevance to replace LSTMs for various forecasting models.