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Low-Rank Embedded Ensemble Semantic Dictionary for Zero-Shot Learning

CVPR 2017 · Label-efficient and robust learning › Zero-/few-shot and meta-learning · approach: Transductive and semantic-dictionary zero-shot · 135 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
use LESD with a VGG-VeryDeep-19 feature representationzero-shot classification · aP&aYaccuracy: 53.2 -> 55.2Helped
use LESD with a VGG-VeryDeep-19 feature representationzero-shot classification · AwAaccuracy: 80.5 -> 82.8Helped
use LESD with a VGG-VeryDeep-19 feature representationzero-shot classification · CUBaccuracy: 43.7 -> 45.2Helped
use LESD with a VGG-VeryDeep-19 feature representationzero-shot classification · SUNaccuracy: 84.4 -> 86.0Helped
use LESD with AlexNet featureszero-shot classification · aP&aYaccuracy: 46.1 -> 48.9Helped
use LESD with AlexNet featureszero-shot classification · AwAaccuracy: 73.2 -> 71.4Hurt
use LESD with AlexNet featureszero-shot classification · CUBaccuracy: 47.1 -> 43.9Hurt
use LESD with AlexNet featureszero-shot classification · SUNaccuracy: 75.5 -> 77.1Helped
use LESD with GoogLeNet featureszero-shot classification · AwAaccuracy: 72.9 -> 76.6Helped
use LESD with GoogLeNet featureszero-shot classification · CUBaccuracy: 54.5 -> 56.2Helped
use LESD with GoogLeNet featureszero-shot classification · SUNaccuracy: 90.0 -> 88.3Hurt
increase the number of seen classes from 50 to 100 or 150LESD on CUB with 50 unseen classes · CUBaccuracy: 40.2 -> 51.2; 40.2 -> 55.9Helped

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