Abstract:Visual sentiment recognition is a challenging task with scientific significance in probing vision-processing mechanisms. Recent approaches mainly focused on using overall images or precise annotations to learn emotional representations, yet neglected to capture abstract semantics from regional information, or led to a heavy annotation burden. In this paper, we propose an end-to-end weakly supervised framework, called Dual Coding Network (DCNet), which models a dual coding process for both shallow features and … Show more
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