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UAST: Uncertainty-Aware Siamese Tracking

ICML 2022 · Probabilistic and scientific modeling › Uncertainty and Gaussian processes · approach: Priors and functional variational uncertainty

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Replace Dirac delta regression with general discretized distribution regression (ablation)Ocean-based anchor-free tracker · GOT-10k testAO: +1.2 points (0.572 to 0.584)Helped
Add distribution focal loss (DFL) (ablation)General distribution regression · GOT-10k testAO: +1.2 points (0.584 to 0.596)Helped
Add joint classification-quality representation head (ablation)UAST ablation · GOT-10k testAO: +1.8 points (0.596 to 0.614); SR0.75 +2.3Helped
Add task alignment sub-network for localization quality features (ablation)UAST ablation · GOT-10k testAO: +2.1 points (0.614 to 0.635)Helped
Use DIoU as localization quality label for joint head instead of centerness or IoU (ablation)Joint representation head · GOT-10k testAO: 0.596 vs 0.587 (centerness) and 0.591 (IoU)Helped
Integrate distributed regression and JCR into anchor-free trackers (SiamCAR, SiamBAN, SiamGAT, Ocean)SiamCAR, SiamBAN, SiamGAT, Ocean · LaSOT testAUC: +3.6 (SiamCAR), +3.4 (SiamBAN), +2.8 (SiamGAT), +4.5 (Ocean)Helped
Integrate UAST components into anchor-free trackers without changing FPSSiamCAR, SiamBAN, SiamGAT, Ocean · LaSOT testFPS: identical FPS before and after (52, 40, 70, 68)No clear effect

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