Cross-Attention is Not Always Needed: Dynamic Cross-Attention for Audio-Visual Dimensional Emotion Recognition

• URL: http://arxiv.org/abs/2403.19554v1
• Date: Thu, 28 Mar 2024 16:38:04 GMT
• Title: Cross-Attention is Not Always Needed: Dynamic Cross-Attention for Audio-Visual Dimensional Emotion Recognition
• Authors: R. Gnana Praveen, Jahangir Alam,
• Abstract summary: We propose Dynamic Cross-Attention (DCA) that can dynamically select cross-attended or unattended features on the fly. We evaluate the performance of the proposed approach on the challenging RECOLA and Aff-Wild2 datasets.
• Score: 3.5803801804085347
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: In video-based emotion recognition, audio and visual modalities are often expected to have a complementary relationship, which is widely explored using cross-attention. However, they may also exhibit weak complementary relationships, resulting in poor representations of audio-visual features, thus degrading the performance of the system. To address this issue, we propose Dynamic Cross-Attention (DCA) that can dynamically select cross-attended or unattended features on the fly based on their strong or weak complementary relationship with each other, respectively. Specifically, a simple yet efficient gating layer is designed to evaluate the contribution of the cross-attention mechanism and choose cross-attended features only when they exhibit a strong complementary relationship, otherwise unattended features. We evaluate the performance of the proposed approach on the challenging RECOLA and Aff-Wild2 datasets. We also compare the proposed approach with other variants of cross-attention and show that the proposed model consistently improves the performance on both datasets.

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