arXiv Open Access 2024

Efficient Audio-Visual Fusion for Video Classification

Mahrukh Awan Asmar Nadeem Armin Mustafa

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Abstrak

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.

Topik & Kata Kunci

cs.CV

Penulis (3)

Mahrukh Awan

Asmar Nadeem

Armin Mustafa

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APA MLA BibTeX

Awan, M., Nadeem, A., Mustafa, A. (2024). Efficient Audio-Visual Fusion for Video Classification. https://arxiv.org/abs/2411.05603

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Informasi Jurnal

Tahun Terbit: 2024
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓