Web: http://arxiv.org/abs/2111.14182

Sept. 20, 2022, 1:13 a.m. | Yu Hsuan Li, Tzu-Yin Chao, Ching-Chun Huang, Pin-Yu Chen, Wei-Chen Chiu

cs.CV updates on arXiv.org arxiv.org

Most of the existing algorithms for zero-shot classification problems
typically rely on the attribute-based semantic relations among categories to
realize the classification of novel categories without observing any of their
instances. However, training the zero-shot classification models still requires
attribute labeling for each class (or even instance) in the training dataset,
which is also expensive. To this end, in this paper, we bring up a new problem
scenario: "Can we derive zero-shot learning for novel attribute
detectors/classifiers and use them …

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