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LOOK, LISTEN AND PAY MORE ATTENTION: FUSING MULTI-MODAL INFORMATION FOR VIDEO VIOLENCE DETECTION
![](https://sigport.org/sites/default/files/styles/home/public/ICASSP_2022_0.jpg?itok=_WnBJxvM)
- Citation Author(s):
- Submitted by:
- Donglai Wei
- Last updated:
- 5 May 2022 - 9:42am
- Document Type:
- Poster
- Document Year:
- 2022
- Event:
- Presenters:
- Donglai Wei
- Paper Code:
- IVMSP-13.3
- Categories:
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Violence detection is an essential and challenging problem in the computer vision community. Most existing works focus on single modal data analysis, which is not effective when multi-modality is available. Therefore, we propose a twostage multi-modal information fusion method for violence detection: 1) the first stage adopts multiple instance learning strategies to refine video-level hard labels into clip-level soft labels, and 2) the next stage uses multi-modal information fused attention module to achieve fusion, and supervised learning is carried out using the soft labels generated at the first stage. Extensive empirical evidence on the XD-Violence dataset shows that our method outperforms the state-of-theart methods.