Paper Publications
Release time: 2026-03-31Hits:
- DOI number:10.1016/j.neucom.2025.132575
- Journal:Neurocomputing
- Key Words:Audio-visual fusion Deep learning Multimodal Survey
- Abstract:With the development of society, audio and video have become predominant forms of media in our daily lives. Current audio-visual fusion (AVF) survey papers are classified according to fusion stages or application scenarios. Although they introduce the development and analyze the performance of different AVF-based methods, the survey papers overlook the impact of fundamental AVF techniques. In this paper, we review the development of AVF-based methods in terms of their fusion techniques and application scenarios. Meanwhile, we provide a comprehensive survey on three major AVF-based applications. Furthermore, we present the results of representative algorithms and analyze their performance to build a deeper understanding of these methods. Finally, we summarize the ongoing challenges and issues in the AVF domain and offer insights into future research problems and directions. We aim to provide a fine-grained classification of AVF and serve as a comprehensive reference for researchers in the AVF domain.
- Indexed by:Journal paper
- Document Type:J
- Volume:671,132575
- Translation or Not:no
- Date of Publication:2026-03-31
- Included Journals:SCI
MOBILE Version