Paper ID: 2411.05603

Efficient Audio-Visual Fusion for Video Classification

Mahrukh Awan, Asmar Nadeem, Armin Mustafa

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.

Submitted: Nov 8, 2024