In this paper, we investigate a problem of predicting what images are likely to appear on the Web at a future time point, given a query word and a database of historical image str...
In crowdsourced relevance judging, each crowd worker typically judges only a small number of examples, yielding a sparse and imbalanced set of judgments in which relatively few wo...
In this paper, we propose a temporal super resolution approach for quasi-periodic image sequence such as human gait. The proposed method effectively combines examplebased and reco...
Naoki Akae, Al Mansur, Yasushi Makihara, Yasushi Y...
Much work has been done on predicting where is one going to be in the immediate future, typically within the next hour. By contrast, we address the open problem of predicting huma...
We extend a recently developed method [1] for learning the semantics of image databases using text and pictures. We incorporate statistical natural language processing in order to...