News Finding: It is an important step toward general artificial intelligence systems -- computers that learn on their own, are intuitive, make decisions based on reasoning and interact with humans in a more human-like way.
Paper Finding: Such templates, however, do not constitute detailed object prototypes of the kind illustrated in Fig.
News Context: It is an important step toward general artificial intelligence systems -- computers that learn on their own, are intuitive, make decisions based on reasoning and interact with humans in a more human-like way. Computers, of course, also cannot explain their rationale for determining what the object in a photo represents: AI-based systems do not build an internal picture or a common-sense model of learned objects the way humans do. "That contextual learning is a key feature of our brains, and it helps us build robust models of objects that are part of an integrated worldview where everything is functionally connected."
Paper Context: Note that the ingenious Poselets approach is based on processing manually tagged data to generate hundreds of distinctive templates (and associated classifiers obtained through extensive supervised training) that have exemplars with various views/poses and scales embedded in them. Such templates, however, do not constitute detailed object prototypes of the kind illustrated in Fig. 1 .The slightly lower recall rate in our model is to be expected as the weak kNN classifer misses many of the viewlets that are otherwise present in an image.