Microsoft COCO: Common Objects in Context

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Microsoft coco : Common Objects in ContextTsung-Yi Lin1, Michael Maire2, Serge Belongie1, James Hays3, Pietro Perona2,Deva Ramanan4, Piotr Doll ar5, C. Lawrence Zitnick51Cornell,2Caltech,3Brown,4UC Irvine,5Microsoft present a new dataset with the goal of advancing thestate-of-the-art in object recognition by placing the question of objectrecognition in the Context of the broader question of scene understand-ing. This is achieved by gathering images of complex everyday scenescontaining Common Objects in their natural Context . Objects are labeledusing per-instance segmentations to aid in precise object dataset contains photos of 91 Objects types that would be easilyrecognizable by a 4 year old. With a total of million labeled in-stances in 328k images, the creation of our dataset drew upon extensivecrowd worker involvement via novel user interfaces for category detec-tion, instance spotting and instance segmentation.

truth stereo and optical ow datasets [20,21] helped stimulate a ood of interest in these areas. The early evolution of object recognition datasets [22,23,24] facil-itated the direct comparison of hundreds of image recognition algorithms while simultaneously pushing the eld towards more complex problems. Recently, the

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