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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 30 / No. 1: Thirtieth AAAI Conference On Artificial Intelligence

Learning Cross-Domain Neural Networks for Sketch-Based 3D Shape Retrieval

March 8, 2023

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Authors

Fan Zhu

New York University Abu Dhabi


Jin Xie

New York University Abu Dhabi


Yi Fang

New York University Abu Dhabi


DOI:

10.1609/aaai.v30i1.10444


Abstract:

Sketch-based 3D shape retrieval, which returns a set of relevant 3D shapes based on users' input sketch queries, has been receiving increasing attentions in both graphics community and vision community. In this work, we address the sketch-based 3D shape retrieval problem with a novel Cross-Domain Neural Networks (CDNN) approach, which is further extended to Pyramid Cross-Domain Neural Networks (PCDNN) by cooperating with a hierarchical structure. In order to alleviate the discrepancies between sketch features and 3D shape features, a neural network pair that forces identical representations at the target layer for instances of the same class is trained for sketches and 3D shapes respectively. By constructing cross-domain neural networks at multiple pyramid levels, a many-to-one relationship is established between a 3D shape feature and sketch features extracted from different scales. We evaluate the effectiveness of both CDNN and PCDNN approach on the extended large-scale SHREC 2014 benchmark and compare with some other well established methods. Experimental results suggest that both CDNN and PCDNN can outperform state-of-the-art performance, where PCDNN can further improve CDNN when employing a hierarchical structure.

Topics: AAAI

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HOW TO CITE:

Fan Zhu|| Jin Xie|| Yi Fang Learning Cross-Domain Neural Networks for Sketch-Based 3D Shape Retrieval Proceedings of the AAAI Conference on Artificial Intelligence, 30 (2016) .

Fan Zhu|| Jin Xie|| Yi Fang Learning Cross-Domain Neural Networks for Sketch-Based 3D Shape Retrieval AAAI 2016, .

Fan Zhu|| Jin Xie|| Yi Fang (2016). Learning Cross-Domain Neural Networks for Sketch-Based 3D Shape Retrieval. Proceedings of the AAAI Conference on Artificial Intelligence, 30, .

Fan Zhu|| Jin Xie|| Yi Fang. Learning Cross-Domain Neural Networks for Sketch-Based 3D Shape Retrieval. Proceedings of the AAAI Conference on Artificial Intelligence, 30 2016 p..

Fan Zhu|| Jin Xie|| Yi Fang. 2016. Learning Cross-Domain Neural Networks for Sketch-Based 3D Shape Retrieval. "Proceedings of the AAAI Conference on Artificial Intelligence, 30". .

Fan Zhu|| Jin Xie|| Yi Fang. (2016) "Learning Cross-Domain Neural Networks for Sketch-Based 3D Shape Retrieval", Proceedings of the AAAI Conference on Artificial Intelligence, 30, p.

Fan Zhu|| Jin Xie|| Yi Fang, "Learning Cross-Domain Neural Networks for Sketch-Based 3D Shape Retrieval", AAAI, p., 2016.

Fan Zhu|| Jin Xie|| Yi Fang. "Learning Cross-Domain Neural Networks for Sketch-Based 3D Shape Retrieval". Proceedings of the AAAI Conference on Artificial Intelligence, 30, 2016, p..

Fan Zhu|| Jin Xie|| Yi Fang. "Learning Cross-Domain Neural Networks for Sketch-Based 3D Shape Retrieval". Proceedings of the AAAI Conference on Artificial Intelligence, 30, (2016): .

Fan Zhu|| Jin Xie|| Yi Fang. Learning Cross-Domain Neural Networks for Sketch-Based 3D Shape Retrieval. AAAI[Internet]. 2016[cited 2023]; .


ISSN: 2374-3468


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