Deep Audio-visual Learning: A Survey

Hao Zhu, Man-Di Luo, Rui Wang, Ai-Hua Zheng, Ran He
2021 International Journal of Automation and Computing  
AbstractAudio-visual learning, aimed at exploiting the relationship between audio and visual modalities, has drawn considerable attention since deep learning started to be used successfully. Researchers tend to leverage these two modalities to improve the performance of previously considered single-modality tasks or address new challenging problems. In this paper, we provide a comprehensive survey of recent audio-visual learning development. We divide the current audio-visual learning tasks
more » ... four different subfields: audio-visual separation and localization, audio-visual correspondence learning, audio-visual generation, and audio-visual representation learning. State-of-the-art methods, as well as the remaining challenges of each subfield, are further discussed. Finally, we summarize the commonly used datasets and challenges.
doi:10.1007/s11633-021-1293-0 fatcat:an5lfyf4m5fh7mlngmdcbx7joy