Self-supervised audiovisual representation learning for remote sensing data

Author:

Heidler Konrad,Mou Lichao,Hu Di,Jin Pu,Li Guangyao,Gan Chuang,Wen Ji-Rong,Zhu Xiao XiangORCID

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Computers in Earth Sciences,Earth-Surface Processes,Global and Planetary Change

Reference59 articles.

1. Alwassel, H., Mahajan, D., Korbar, B., Torresani, L., Ghanem, B., Tran, D., 2020. Self-Supervised Learning by Cross-Modal Audio-Video Clustering. In: Proc. Adv. Neural Inf. Process. Syst., Vol. 33. pp. 9758–9770.

2. Arandjelovic, R., Zisserman, A., 2017. Look, listen and learn. In: Proc. IEEE Int. Conf. Comput. Vis.. pp. 609–617.

3. Aytar, Y., Vondrick, C., Torralba, A., 2016. SoundNet: Learning sound representations from unlabeled video. In: Proc. Adv. Neural Inf. Process. Syst., Vol. 29. pp. 892–900.

4. See, hear, and read: Deep aligned representations;Aytar,2017

5. Geography-Aware Self-Supervised Learning;Ayush,2020

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