CRFTrack_:

TUD-Crossing


Benchmark:

Short name:

CRFTrack_

Detector:

Public

Description:

n/a

Reference:

Jun xiang, Chao Ma, Guohan Xu, Jianhua Hou, End-to-End Learning Deep CRF models for Multi-Object Tracking. In IEEE Transactions on Circuits and Systems for Video Technology, 2020

Last submitted:

June 25, 2019 (1 year ago)

Published:

June 26, 2019 at 11:13:54 CET

Submissions:

1

Project page / code:

n/a

Open source:

Yes

Hardware:

2.5GHZ

Runtime:

3.2 Hz

Benchmark performance:

Sequence MOTA IDF1 MOTP MT ML FP FN Recall Precision FAF ID Sw. Frag
2D MOT 201540.049.671.9166 (23.0)206 (28.6)10,29525,91757.877.51.8658 (11.4)1,508 (26.1)

Detailed performance:

Sequence MOTA IDF1 MOTP MT ML FP FN Recall Precision FAF ID Sw. Frag
ADL-Rundle-121.843.470.71123,7563,44563.060.97.575176
ADL-Rundle-338.245.175.8681,5684,62354.577.92.592124
AVG-TownCentre49.063.368.766437782,78961.084.91.775353
ETH-Crossing31.952.176.581112655344.978.10.649
ETH-Jelmoli48.566.476.2161344085766.279.21.0946
ETH-Linthescher34.646.678.2211142525,56137.793.00.22871
KITTI-1651.666.171.74118461763.785.50.92256
KITTI-1939.858.167.99109002,26757.677.40.952201
PETS09-S2L251.030.969.4931,0733,37065.085.42.5282393
TUD-Crossing80.888.870.21004216385.295.70.2725
Venice-137.360.171.4611,1761,67263.471.12.61254

Raw data: