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A Berkeley View of Systems Challenges for AI Ion Stoica Dawn Song Raluca Ada Popa David A. Patterson Michael W. Mahoney Randy H. Katz Anthony D. Joseph Michael Jordan Joseph M. Hellerstein Joseph Gonzalez Ken Goldberg Ali Ghodsi David E. Culler Pieter Abbeel Electrical Engineering and Computer Sciences University of California at Berkeley Technical Report No. UCB/EECS-2017-159 http://www2.eecs.ber

Contour Detection and Image Segmentation Resources Overview The goal of this work is to provide an empirical basis for research on image segmentation and boundary detection. In order to promote scientific progress in the study of visual grouping, we provide the following resources: A large dataset of natural images that have been manually segmented. The human annotations serve as ground truth for

New: The BSDS500, an extended version of the BSDS300 that includes 200 fresh test images, is now available here. The goal of this work is to provide an empirical basis for research on image segmentation and boundary detection.  To this end, we have collected 12,000 hand-labeled segmentations of 1,000 Corel dataset images from 30 human subjects.  Half of the segmentations were obtained from present

New: The BSDS500, an extended version of the BSDS300 that includes 200 fresh test images, is now available here. The goal of this work is to provide an empirical basis for research on image segmentation and boundary detection.  To this end, we have collected 12,000 hand-labeled segmentations of 1,000 Corel dataset images from 30 human subjects.  Half of the segmentations were obtained from present