Before revision:  Experimental results on the Trajnet++ benchmark show that the U-LSTM variant can yield better results regarding every available metric (ADE, FDE, Collision rate) than common LSTMs sequence encoders for a variety of approaches and interaction modules  .
After revision:  Experimental results on the Trajnet++ benchmark show that the U-LSTM variant can yield better results regarding every available metric (ADE, FDE, Collision rate) than common LSTMs sequence encoders for a variety of approaches and interaction modules , suggesting that the proposed approach is a viable alternative to the de facto sequence encoding RNNs .