On Aligning Hierarchical Standardized Embedding for Audio-visual Generalized Zero-shot Learning
Audio-visual Generalized Zero-shot Learning (AV-GZSL) is a challenging task that aims to classify both seen and unseen objects or scenes by integrating data from audio and visual modalities. Recent studies primarily focus on fusing or aligning audio and visual features to generate more informative audio-visual embeddings. Also, aligning the audio-visual and textual features of most existing methods relies solely on the optimization objectives. However, those methods neglect the inherent distributional and structural differences between audio-visual and textual modalities. To address this limitation, we propose a method termed Aligning Hierarchical Standardized Embedding (AHSE), which enab...
| Authors | Zihan Zhang, Jie Hong, Siyuan Fan et al. |
|---|---|
| Primary category | cs.CV |
| Published | 10 June 2026 |
| Last updated at source | 10 June 2026 |
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