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A Causal And-Or Graph Model for Visibility Fluent Reasoning in Tracking Interacting Objects

CVPR 2018 · Detection and segmentation › Tracking · approach: Transformer-based video object tracking · 27 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Jointly reason visibility fluents and object locations using the full C-AOG methodHuman tracking · TIO PlazaMOTA: 34.3% -> 46.0%Helped
Jointly reason visibility fluents and object locations using the full C-AOG methodHuman tracking · TIO ParkingLotMOTA: 30.1% -> 38.6%Helped
Add likelihood terms to the prior-only tracking model (ablation)Our-full · TIO PlazaMOTA: 31.9% -> 46.0%Helped
Add likelihood terms to the prior-only tracking model (ablation)Our-full · TIO ParkingLotMOTA: 28.7% -> 38.6%Helped
Add the vehicle data-likelihood term alongside the human likelihood and prior (ablation)Our-full · TIO PlazaMOTA: 32.5% -> 46.0%Helped
Add the vehicle data-likelihood term alongside the human likelihood and prior (ablation)Our-full · TIO ParkingLotMOTA: 28.9% -> 38.6%Helped

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