Multimodal few-shot classification without attribute embedding

Multimodal few-shot learning aims to exploit complementary information inherent in multiple modalities for vision tasks in low data scenarios. Most of the current research focuses on a suitable embedding space for the various modalities. While solutions based on embedding provide state-of-the-art re...

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Bibliographic Details
Main Authors: Chang, Jun Qing, Rajan, Deepu, Vun, Nicholas
Other Authors: School of Computer Science and Engineering
Format: Article
Language:English
Published: 2024
Subjects:
Online Access:https://hdl.handle.net/10356/175469
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Institution: Nanyang Technological University
Language: English

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