KG-SP: Knowledge Guided Simple Primitives for Open World Compositional 
Zero-Shot Learning

Karthik, Shyamgopal; Mancini, Massimiliano; Akata, Zeynep

doi:10.1109/CVPR52688.2022.00912

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KG-SP: Knowledge Guided Simple Primitives for Open World Compositional Zero-Shot Learning

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Akata, Zeynep
Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society;
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https://doi.org/10.1109/CVPR52688.2022.00912
(Publisher version)

https://doi.org/10.48550/arXiv.2205.06784
(Preprint)

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Karthik, S., Mancini, M., & Akata, Z. (2022). KG-SP: Knowledge Guided Simple Primitives for Open World Compositional Zero-Shot Learning. In 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2022) (pp. 9326-9335). Piscataway, NJ: IEEE. doi:10.1109/CVPR52688.2022.00912.

Cite as: https://hdl.handle.net/21.11116/0000-0010-2F9D-A

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