computer-vision-13
Multi-label Image Recognition with Partial Labels
3260 papers • 126 benchmarks • 313 datasets
Multi-label image recognition with partial labels (MLR-PL), in which some labels are known while others are unknown for each multi-label image, aims to train MLR models with partial labels to reduce the annotation cost. Since existing MLR datasets have complete labels, current works propose to randomly drop a certain proportion of positive and negative labels to create partially annotated datasets, and report the results on the known labels proportion of 10% to 90%.
(Image credit: Papersgraph)
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MS-COCO-2014
MS-COCO-2014
PASCAL VOC 2007
PASCAL VOC 2007
Visual Genome
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