Self-SupervisedMulti-ObjectTrackingwithCross-InputConsistency (SupplementaryMaterial) FavyenBastani,Songtao He,SamMadden

For each training sequence hI0,...,Ini, Only-Occlusion randomly selects four indexes 0 < k1 k2 < k3 k4 < n to construct two disjoint frame subsequences hIk1,...,Ik2i and hIk3,...,Ik4i. Learning to merely compare detection features across consecutive frames would yield low accuracy since features in occluded frames are not observed. This strategy yields high consistency because it is unaffected by occluded intermediate frames. We select two indexes 0 < k5,k6 < n. Then, we randomly pick k5 and k6 such that k3 k5 k4 and k1 k6 k2, i.e., the hand-off for one tracker occurs when the other tracker observes a simulated occlusion.