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Semantic Feature Extraction for Generalized Zero-Shot Learning

AAAI 2022 · Label-efficient and robust learning › Zero-/few-shot and meta-learning · approach: Generative feature synthesis for zero-shot · 53 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add the MI-based loss to reconstruction training (ablation)SE-GZSL · AwA1acc_h: 58.3 -> 65.4Helped
Add the MI-based loss to reconstruction training (ablation)SE-GZSL · AwA2acc_h: 61.6 -> 65.5Helped
Add the MI-based loss to reconstruction training (ablation)SE-GZSL · CUBacc_h: 49.9 -> 55.1Helped
Add the MI-based loss to reconstruction training (ablation)SE-GZSL · SUNacc_h: 39.4 -> 41.3Helped
Add the similarity-based loss to reconstruction and MI training (ablation)SE-GZSL · AwA1acc_h: 65.4 -> 68.1Helped
Add the similarity-based loss to reconstruction and MI training (ablation)SE-GZSL · AwA2acc_h: 65.5 -> 68.8Helped
Add the similarity-based loss to reconstruction and MI training (ablation)SE-GZSL · CUBacc_h: 55.1 -> 56.4Helped
Add the similarity-based loss to reconstruction and MI training (ablation)SE-GZSL · SUNacc_h: 41.3 -> 43.1Helped
Add a residual encoder to separate attribute-irrelevant information from the semantic representation (ablation)SE-GZSL · AwA1acc_h: 66.7 -> 68.1Helped
Add a residual encoder to separate attribute-irrelevant information from the semantic representation (ablation)SE-GZSL · AwA2acc_h: 67.5 -> 68.8Helped
Add a residual encoder to separate attribute-irrelevant information from the semantic representation (ablation)SE-GZSL · CUBacc_h: 55.1 -> 56.4Helped
Add a residual encoder to separate attribute-irrelevant information from the semantic representation (ablation)SE-GZSL · SUNacc_h: 42.1 -> 43.1Helped

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