StreamingFlow: Streaming Occupancy Forecasting with Asynchronous Multi-modal Data Streams via Neural Ordinary Differential Equation

arXiv:2302.09585v2 Announce Type: replace
Abstract: Predicting the future occupancy states of the surrounding environment is a vital task for autonomous driving. However, current best-performing single-modality methods or multi-modality fusion perception methods are only able to predict uniform snapshots of future occupancy states and require strictly synchronized sensory data for sensor fusion. We propose a novel framework, StreamingFlow, to lift these strong limitations. StreamingFlow is a novel BEV occupancy predictor that ingests asynchronous multi-sensor data streams for fusion and performs streaming …

abstract arxiv asynchronous autonomous autonomous driving cs.cv current data data streams differential differential equation driving environment equation forecasting fusion future however modal multi-modal ordinary perception replace snapshots streaming type uniform via vital