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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 35 / No. 3: AAAI-21 Technical Tracks 3

Task-Independent Knowledge Makes for Transferable Representations for Generalized Zero-Shot Learning

February 1, 2023

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Authors

Chaoqun Wang

School of Data Science, University of Science and Technology of China, Hefei, Anhui, China The National Engineering Laboratory for Brain-inspired Intelligence Technology and Application, University of Science and Technology of China, Hefei, Anhui, China


Xuejin Chen

School of Data Science, University of Science and Technology of China, Hefei, Anhui, China The National Engineering Laboratory for Brain-inspired Intelligence Technology and Application, University of Science and Technology of China, Hefei, Anhui, China


Shaobo Min

The National Engineering Laboratory for Brain-inspired Intelligence Technology and Application, University of Science and Technology of China, Hefei, Anhui, China


Xiaoyan Sun

The National Engineering Laboratory for Brain-inspired Intelligence Technology and Application, University of Science and Technology of China, Hefei, Anhui, China


Houqiang Li

School of Data Science, University of Science and Technology of China, Hefei, Anhui, China The National Engineering Laboratory for Brain-inspired Intelligence Technology and Application, University of Science and Technology of China, Hefei, Anhui, China


DOI:

10.1609/aaai.v35i3.16375


Abstract:

Generalized Zero-Shot Learning (GZSL) targets recognizing new categories by learning transferable image representations. Existing methods find that, by aligning image representations with corresponding semantic labels, the semantic-aligned representations can be transferred to unseen categories. However, supervised by only seen category labels, the learned semantic knowledge is highly task-specific, which makes image representations biased towards seen categories. In this paper, we propose a novel Dual-Contrastive Embedding Network (DCEN) that simultaneously learns task-specific and task-independent knowledge via semantic alignment and instance discrimination. First, DCEN leverages task labels to cluster representations of the same semantic category by cross-modal contrastive learning and exploring semantic-visual complementarity. Besides task-specific knowledge, DCEN then introduces task-independent knowledge by attracting representations of different views of the same image and repelling representations of different images. Compared to high-level seen category supervision, this instance discrimination supervision encourages DCEN to capture low-level visual knowledge, which is less biased toward seen categories and alleviates the representation bias. Consequently, the task-specific and task-independent knowledge jointly make for transferable representations of DCEN, which obtains averaged 4.1% improvement on four public benchmarks.

Topics: AAAI

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HOW TO CITE:

Chaoqun Wang||Xuejin Chen||Shaobo Min||Xiaoyan Sun||Houqiang Li Task-Independent Knowledge Makes for Transferable Representations for Generalized Zero-Shot Learning Proceedings of the AAAI Conference on Artificial Intelligence (2021) 2710-2718.

Chaoqun Wang||Xuejin Chen||Shaobo Min||Xiaoyan Sun||Houqiang Li Task-Independent Knowledge Makes for Transferable Representations for Generalized Zero-Shot Learning AAAI 2021, 2710-2718.

Chaoqun Wang||Xuejin Chen||Shaobo Min||Xiaoyan Sun||Houqiang Li (2021). Task-Independent Knowledge Makes for Transferable Representations for Generalized Zero-Shot Learning. Proceedings of the AAAI Conference on Artificial Intelligence, 2710-2718.

Chaoqun Wang||Xuejin Chen||Shaobo Min||Xiaoyan Sun||Houqiang Li. Task-Independent Knowledge Makes for Transferable Representations for Generalized Zero-Shot Learning. Proceedings of the AAAI Conference on Artificial Intelligence 2021 p.2710-2718.

Chaoqun Wang||Xuejin Chen||Shaobo Min||Xiaoyan Sun||Houqiang Li. 2021. Task-Independent Knowledge Makes for Transferable Representations for Generalized Zero-Shot Learning. "Proceedings of the AAAI Conference on Artificial Intelligence". 2710-2718.

Chaoqun Wang||Xuejin Chen||Shaobo Min||Xiaoyan Sun||Houqiang Li. (2021) "Task-Independent Knowledge Makes for Transferable Representations for Generalized Zero-Shot Learning", Proceedings of the AAAI Conference on Artificial Intelligence, p.2710-2718

Chaoqun Wang||Xuejin Chen||Shaobo Min||Xiaoyan Sun||Houqiang Li, "Task-Independent Knowledge Makes for Transferable Representations for Generalized Zero-Shot Learning", AAAI, p.2710-2718, 2021.

Chaoqun Wang||Xuejin Chen||Shaobo Min||Xiaoyan Sun||Houqiang Li. "Task-Independent Knowledge Makes for Transferable Representations for Generalized Zero-Shot Learning". Proceedings of the AAAI Conference on Artificial Intelligence, 2021, p.2710-2718.

Chaoqun Wang||Xuejin Chen||Shaobo Min||Xiaoyan Sun||Houqiang Li. "Task-Independent Knowledge Makes for Transferable Representations for Generalized Zero-Shot Learning". Proceedings of the AAAI Conference on Artificial Intelligence, (2021): 2710-2718.

Chaoqun Wang||Xuejin Chen||Shaobo Min||Xiaoyan Sun||Houqiang Li. Task-Independent Knowledge Makes for Transferable Representations for Generalized Zero-Shot Learning. AAAI[Internet]. 2021[cited 2023]; 2710-2718.


ISSN: 2374-3468


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