Supplementary Information: TrackingWithout Re-recognitioninHumansandMachines

In this work we tested a relatively small number ofPathTracker versions. We mostly focused on small variations to the number of distractors and video length, but in future work we hope to incorporate other variations like speed and velocity manipulations, and generalization across temporalvariations[1]. One potential issue is determining when a visual system should rely on appearance-based vs. appearance-free features for tracking. Our solution is two-pronged and potentially insufficient. The first strategy is for top-down feedback from the TransT into the InT,which we aligns tracks between the two models.