Hierarchical confidence calibration and LoCLIP adaptation improve pseudo-label quality for open-vocabulary object detection, achieving new state-of-the-art results on COCO and LVIS benchmarks.
Probabilistic two-stage detection
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
UNVERDICTED 2representative citing papers
A two-stage nnUNet framework with patient-specific signed distance maps and wall-masked loss achieves 61.1% Dice and 1.711 mm ASSD for left atrial scar segmentation on the LAScarQS 2022 dataset.
citing papers explorer
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Exploring Hierarchical Consistency and Unbiased Objectness for Open-Vocabulary Object Detection
Hierarchical confidence calibration and LoCLIP adaptation improve pseudo-label quality for open-vocabulary object detection, achieving new state-of-the-art results on COCO and LVIS benchmarks.
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A Two Stage Pipeline for Left Atrial Wall Constrained Scar Segmentation and Localization from LGE-MR Images
A two-stage nnUNet framework with patient-specific signed distance maps and wall-masked loss achieves 61.1% Dice and 1.711 mm ASSD for left atrial scar segmentation on the LAScarQS 2022 dataset.