From Easy to Hard: Learning Language-Guided Curriculum for Visual Question Answering on Remote Sensing Data-Reference-Cited by-同舟云学术

From Easy to Hard: Learning Language-Guided Curriculum for Visual Question Answering on Remote Sensing Data

Published:2022 Issue: Volume:60 Page:1-11
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Yuan Zhenghang¹,Mou Lichao²^ORCID,Wang Qi³^ORCID,Zhu Xiao Xiang²^ORCID

Affiliation:

1. Chair of Data Science in Earth Observation [former: Signal Processing in Earth Observation (SiPEO)], Technical University of Munich (TUM), Munich, Germany

2. Remote Sensing Technology Institute (IMF), German Aerospace Center (DLR), Weßling, Germany

3. School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi’an, China

Funder

Helmholtz Association

Bundesministerium fr Bildung und Forschung

H2020 European Research Council

China Scholarship Council

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/9633014/09771224.pdf?arnumber=9771224

Reference55 articles.

1. Faster R-CNN: Towards real-time object detection with region proposal networks;ren;arXiv 1506 01497,2015

2. Beyond Bilinear: Generalized Multimodal Factorized High-Order Pooling for Visual Question Answering

3. Multi-grained Attention with Object-level Grounding for Visual Question Answering

4. Improving Visual Question Answering by Referring to Generated Paragraph Captions

5. A multi-world approach to question answering about real-world scenes based on uncertain input;malinowski;arXiv 1410 0210,2014

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