Attending to Discriminative Certainty for Domain Adaptation

CVPR 2019 Vinod Kumar KurmiShanu KumarVinay P Namboodiri

In this paper, we aim to solve for unsupervised domain adaptation of classifiers where we have access to label information for the source domain while these are not available for a target domain. While various methods have been proposed for solving these including adversarial discriminator based methods, most approaches have focused on the entire image based domain adaptation... (read more)

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Results from the Paper


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT LEADERBOARD
Domain Adaptation ImageCLEF-DA CADA-P Accuracy 88.3 # 4
Domain Adaptation Office-31 CADA-P Average Accuracy 89.5 # 5
Domain Adaptation Office-Home CADA Accuracy 70.2 # 4