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cs.CV2021
Multi-label Classification with Partial Annotations using Class-aware Selective Loss
Emanuel Ben-Baruch, Tal Ridnik, Itamar Friedman +4
Large-scale multi-label classification datasets are commonly, and perhaps inevitably, partially annotated. That is, only a small subset of labels are annotated per sample. Differen…
cs.CV2021
Semantic Diversity Learning for Zero-Shot Multi-label Classification
Avi Ben-Cohen, Nadav Zamir, Emanuel Ben Baruch +2
Training a neural network model for recognizing multiple labels associated with an image, including identifying unseen labels, is challenging, especially for images that portray nu…