AFTrack: Adaptive Kalman Filter and Information Fusion for Tracking


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Rendering of new sequences is currently deactivated due to heavy load.

Rendering of new sequences is currently deactivated due to heavy load.

Benchmark:

MOT20 | MOT17 |

Short name:

AFTrack

Detector:

Private

Description:

We used YOLOX detector and SBS50 feature extraction model, with a detection threshold set to 0.6, and trained using the first half of the MOT17 and MOT20 training sets for 60 rounds.

Reference:

Last submitted:

January 28, 2024 (2 months ago)

Published:

January 28, 2024 at 15:44:32 CET

Submissions:

2

Project page / code:

n/a

Open source:

No

Hardware:

3.80GHz,4 Core

Runtime:

1.7 Hz

Benchmark performance:

Sequence MOTA IDF1 HOTA MT ML FP FN Rcll Prcn AssA DetA AssRe AssPr DetRe DetPr LocA FAF ID Sw. Frag
MOT2078.077.863.5870 (70.0)118 (9.5)24,59787,94083.094.663.264.169.078.269.579.284.05.51,039 (0.0)1,108 (0.0)

Detailed performance:

Sequence MOTA IDF1 HOTA MT ML FP FN Rcll Prcn AssA DetA AssRe AssPr DetRe DetPr LocA FAF ID Sw. Frag
MOT20-0487.986.870.95701911,98520,78792.495.569.772.375.580.678.280.884.65.8256326
MOT20-0666.666.153.5145586,47437,46771.893.652.754.558.472.859.177.183.06.4414386
MOT20-0781.775.465.28832,0443,89188.293.561.769.667.179.376.480.985.73.5117109
MOT20-0861.163.349.567384,09425,79566.792.749.749.555.373.453.974.882.05.1252287

Raw data:


AFTrack