CVLGJun 13, 2022

The Modality Focusing Hypothesis: Towards Understanding Crossmodal Knowledge Distillation

arXiv:2206.06487v365 citationsh-index: 16
Originality Incremental advance
AI Analysis

This addresses the problem of understanding and improving crossmodal knowledge transfer for researchers in multimodal learning, though it is incremental as it builds on prior empirical successes.

The paper investigates the working mechanism of crossmodal knowledge distillation, finding it is not universally effective and proposing a modality focusing hypothesis to explain its efficacy, supported by experiments on 6 multimodal datasets.

Crossmodal knowledge distillation (KD) extends traditional knowledge distillation to the area of multimodal learning and demonstrates great success in various applications. To achieve knowledge transfer across modalities, a pretrained network from one modality is adopted as the teacher to provide supervision signals to a student network learning from another modality. In contrast to the empirical success reported in prior works, the working mechanism of crossmodal KD remains a mystery. In this paper, we present a thorough understanding of crossmodal KD. We begin with two case studies and demonstrate that KD is not a universal cure in crossmodal knowledge transfer. We then present the modality Venn diagram to understand modality relationships and the modality focusing hypothesis revealing the decisive factor in the efficacy of crossmodal KD. Experimental results on 6 multimodal datasets help justify our hypothesis, diagnose failure cases, and point directions to improve crossmodal knowledge transfer in the future.

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