Method

WMOTS [WMOTS]
[Anonymous Submission]

Submitted on 29 Oct. 2021 08:33 by
[Anonymous Submission]

Running time:0.2 s
Environment:1 core @ 2.5 Ghz (Python)

Method Description:
WMOTS
Parameters:
Dataset = MOTS
Method = X
a = 0.3
b = 0.2
Network = R50
Latex Bibtex:

Detailed Results

From all 29 test sequences, our benchmark computes the HOTA tracking metrics (HOTA, DetA, AssA, DetRe, DetPr, AssRe, AssPr, LocA) [1] as well as the CLEARMOT, MT/PT/ML, identity switches, and fragmentation [2,3] metrics. The tables below show all of these metrics.


Benchmark HOTA DetA AssA DetRe DetPr AssRe AssPr LocA
CAR 59.65 % 66.78 % 54.22 % 72.92 % 79.82 % 57.67 % 84.93 % 84.66 %
PEDESTRIAN 42.80 % 49.48 % 39.23 % 54.35 % 68.41 % 42.90 % 73.98 % 76.74 %

Benchmark TP FP FN
CAR 31362 5398 2220
PEDESTRIAN 14690 6007 1755

Benchmark MOTSA MOTSP MODSA IDSW sMOTSA
CAR 76.50 % 82.66 % 79.28 % 1021 61.70 %
PEDESTRIAN 58.66 % 72.79 % 62.50 % 794 39.35 %

Benchmark MT rate PT rate ML rate FRAG
CAR 71.17 % 27.03 % 1.80 % 943
PEDESTRIAN 39.63 % 48.52 % 11.85 % 929

Benchmark # Dets # Tracks
CAR 33582 1642
PEDESTRIAN 16445 993

This table as LaTeX