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Spatial Feature Calibration and Temporal Fusion for Effective One-Stage Video Instance Segmentation

CVPR 2021 · Video › Video segmentation and tracking · approach: Video semantic and panoptic segmentation · 48 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add feature calibration for anchors using larger aspect-ratio-specific kernels (ablation)Yolact · YouTube-VIS validAP: 28.9 -> 30.8Helped
Use FCA with smaller aspect-ratio-specific kernels (ablation)Yolact · YouTube-VIS validAP: +1%Helped
Add adaptive bounding-box feature calibration (ablation)Baseline · YouTube-VIS validAP: +2.3%Helped
Add aligned bounding-box feature calibration (ablation)Baseline · YouTube-VIS validAP: +2.4%Helped
Add temporal fusion (ablation)Baseline · YouTube-VIS validAP: +5.2%Helped
Add adaptive FCB after FCA (ablation)Yolact + FCA · YouTube-VIS validAP: 30.8 -> 34.4Helped
Add aligned FCB after FCA (ablation)Yolact + FCA · YouTube-VIS validAP: 30.8 -> 33.1Helped
Add temporal fusion to FCA plus adaptive FCB (ablation)Yolact + FCA + FCB (ada) · YouTube-VIS validAP: 34.4 -> 36.8Helped
Add temporal fusion to FCA plus aligned FCB (ablation)Yolact + FCA + FCB (ali) · YouTube-VIS validAP: 33.1 -> 36.3Helped
Use adaptive rather than aligned FCB features (ablation)STMask · YouTube-VIS validAP: 36.3 -> 36.8Mixed
Calibrate classification, mask, and tracking branches together with adaptive features (ablation)Baseline + FCA · YouTube-VIS validAP: 30.8 -> 33.7Helped
Calibrate only classification and mask branches with adaptive features (ablation)Baseline + FCA · YouTube-VIS validAP: 30.8 -> 34.4Helped

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