Visual and audio scene classification for detecting discrepancies in video: a baseline method and experimental protocol

• URL: http://arxiv.org/abs/2405.00384v1
• Date: Wed, 1 May 2024 08:30:58 GMT
• Title: Visual and audio scene classification for detecting discrepancies in video: a baseline method and experimental protocol
• Authors: Konstantinos Apostolidis, Jakob Abesser, Luca Cuccovillo, Vasileios Mezaris,
• Abstract summary: We first design and optimize an audio-visual scene classifier, to compare with existing classification baselines that use both modalities. By applying this classifier separately to the audio and the visual modality, we can detect scene-class inconsistencies between them. Our approach achieves state-of-the-art results in scene classification and promising outcomes in audio-visual discrepancies detection.
• Score: 6.749750044497733
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This paper presents a baseline approach and an experimental protocol for a specific content verification problem: detecting discrepancies between the audio and video modalities in multimedia content. We first design and optimize an audio-visual scene classifier, to compare with existing classification baselines that use both modalities. Then, by applying this classifier separately to the audio and the visual modality, we can detect scene-class inconsistencies between them. To facilitate further research and provide a common evaluation platform, we introduce an experimental protocol and a benchmark dataset simulating such inconsistencies. Our approach achieves state-of-the-art results in scene classification and promising outcomes in audio-visual discrepancies detection, highlighting its potential in content verification applications.

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