Efficient Audio-Visual Fusion for Video Classification

• URL: http://arxiv.org/abs/2411.05603v1
• Date: Fri, 08 Nov 2024 14:47:28 GMT
• Title: Efficient Audio-Visual Fusion for Video Classification
• Authors: Mahrukh Awan, Asmar Nadeem, Armin Mustafa,
• Abstract summary: We present Attend-Fusion, a novel and efficient approach for audio-visual fusion in video classification tasks. Our method addresses the challenge of exploiting both audio and visual modalities while maintaining a compact model architecture.
• Score: 6.106447284305316
• License:
• Abstract: We present Attend-Fusion, a novel and efficient approach for audio-visual fusion in video classification tasks. Our method addresses the challenge of exploiting both audio and visual modalities while maintaining a compact model architecture. Through extensive experiments on the YouTube-8M dataset, we demonstrate that our Attend-Fusion achieves competitive performance with significantly reduced model complexity compared to larger baseline models.

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