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Class structure‐aware adversarial loss for cross‐domain human action recognition
2021
IET Image Processing
Cross-domain action recognition is a challenging vision task due to the domain shift and the absence of labeled data in the target domain. With only labelled source domain and unlabelled target domain data during training, some existing methods rely on an adversarial framework to align the features from different domains to a common latent space. However, the existing adversarial-based approaches have a major limitation of only attempting to perform the alignment from a holistic view, ignoring
doi:10.1049/ipr2.12309
fatcat:kaptzeq54rbalbxi6wcwrskwfa