Latent Embedding Feedback and Discriminative Features for Zero-Shot Classification

Zero-shot learning strives to classify unseen categories for which no data is available during training. In the generalized variant, the test samples can further belong to seen or unseen categories... (read more)

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Results from the Paper


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT BENCHMARK
Generalized Zero-Shot Learning AWA2 GZSL_TF-VAEGAN Harmonic mean 66.6 # 1
Zero-Shot Learning AWA2 ZSL_TF-VAEGAN average top-1 classification accuracy 72.2 # 1
Zero-Shot Learning CUB-200-2011 ZSL_TF-VAEGAN average top-1 classification accuracy 64.9 # 1
Generalized Zero-Shot Learning CUB-200-2011 GZSL_TF-VAEGAN Harmonic mean 58.1 # 1
Generalized Zero-Shot Learning Oxford 102 Flower GZSL_TF-VAEGAN Harmonic mean 71.7 # 1
Zero-Shot Learning Oxford 102 Flower ZSL_TF-VAEGAN average top-1 classification accuracy 70.8 # 1
Zero-Shot Learning SUN Attribute ZSL_TF-VAEGAN average top-1 classification accuracy 66 # 1
Generalized Zero-Shot Learning SUN Attribute GZSL_TF-VAEGAN Harmonic mean 43 # 1

Methods used in the Paper


METHOD TYPE
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