Marco Fiore

CloudLSTM: A Recurrent Neural Model for Spatiotemporal Point-cloud Stream Forecasting

This paper introduces CloudLSTM, a new branch of recurrent neural models tailored to forecasting over data streams generated by geospatial point-cloud sources. We design a Dynamic Point-cloud Convolution (DConv) operator as the core component of CloudLSTMs, which performs convolution directly over p…