Abstract:In this paper, we propose a multi-domain learning model for action recognition. The proposed method inserts domain-specific adapters between layers of domainindependent layers of a backbone network. Unlike a multihead network that switches classification heads only, our model switches not only the heads, but also the adapters for facilitating to learn feature representations universal to multiple domains. Unlike prior works, the proposed method is model-agnostic and doesn't assume model structures unlike prior… Show more
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