Model-free detection and tracking of dynamic objects with 2D lidar

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A Survey of Autonomous Driving: Common Practices and Emerging Technologies (2019, background): “Various models have been proposed for vehicles and pedestrians, while some models generalize to any dynamic object [190].”
Deep tracking in the wild: End-to-end tracking using recurrent neural networks (2018, methodology): “The achieved tracking accuracy is superior to the original architecture presented by Ondrúška and Posner (2016), as well as to that of an alternative state-ofthe-art model-free tracking solution targeted at the same problem (Wang et al., 2015).”
Deep Tracking on the Move: Learning to Track the World from a Moving Vehicle using Recurrent Neural Networks (2016, background): “Many tracking systems employ multiple hand-engineered stages (e.g. object detection, semantic classiﬁcation, data association, state estimation and motion modelling, occupancy grid generation) in order to represent the state and evolution of the world ([3], [4], [5]).”