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We present an efficient approximate message passing solver for the lifteddisjoint paths problem (LDP), a natural but NP-hard model for multiple objecttracking (MOT). Our tracker scales to very large instances that come from longand crowded MOT sequences. Our approximate solver enables us to process theMOT15/16/17 benchmarks without sacrificing solution quality and allows forsolving MOT20, which has been out of reach up to now for LDP solvers due to itssize and complexity. On all these four standard MOT benchmarks we achieveperformance comparable or better than current state-of-the-art methodsincluding a tracker based on an optimal LDP solver.

Making Higher Order MOT Scalable: An Efficient Approximate Solver for Lifted Disjoint Paths