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Towards Improving Calibration in Object Detection Under Domain Shift

NeurIPS 2022 · Detection and segmentation › Open-set and few-shot detection · approach: Domain-adaptive object detection · 7 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
add TCD auxiliary loss to FCOSFCOS · CS to CS-foggy OODD-ECE: 18.4 -> 5.5Helped
add TCD auxiliary loss to FCOSFCOS · Sim10K to CSAP@0.5: 37.6 -> 42.4Helped
apply post-hoc temperature scaling to FCOSFCOS · in-domain and OOD detectionsD-ECE: 15.1 -> 25.3Hurt
apply post-hoc temperature scaling to Faster-RCNNFaster-RCNN · Sim10K in-domainD-ECE: 23.7 -> 15.0Helped
add TCD to Faster-RCNNFaster-RCNN · CS to BDD100KD-ECE: 16.3 -> 9.6Helped
add TCD to EPM domain-adaptive detectorEPM · Sim10K to CSD-ECE: 16.0 -> 9.9Helped
add TCD to SWDA two-stage adaptive detectorSWDA · Sim10K to CSAP@0.5: 40.9 -> 40.0Hurt
add TCD to SSAL(UGPL)SSAL(UGPL) · Sim10K to CSD-ECE: 13.6 -> 8.5Helped
add implicit calibration technique (ICT) to SSAL(UGPL) (ablation)SSAL(UGPL) · Sim10K to CSD-ECE: 13.6 -> 12.7Helped
add ICT on top of TCD (ablation)SSAL(UGPL)+TCD · CS to CS-foggyD-ECE: 19.1 -> 16.7Helped
add detection component d_det to TCD (ablation)TCD on FCOS · CS to CS-foggy OODD-ECE: 8.1 -> 5.5Helped
add classification component d_cls to TCD (ablation)TCD on FCOS · CS to CS-foggy OODD-ECE: 13.3 -> 5.5Helped

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