Simultaneous Detection and Segmentation
Simultaneous Detection and Segmentation Bharath Hariharan, Pablo Arbeláez, Ross Girshick, Jitendra Malik. Abstract We aim to detect all instances of a category in an image and, for each instance, mark the pixels that belong to it. We call this task Simultaneous Detection and Segmentation (SDS). Unlike classical bounding box detection, SDS requires a segmentation and not just a box. Unlike classica
A Berkeley View of Systems Challenges for AI
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
Tech Reports | EECS at UC Berkeley
Christopher Celio and Pi-Feng Chiu and Borivoje Nikolic and David A. Patterson and Krste Asanović EECS Department, University of California, Berkeley Technical Report No. UCB/EECS-2017-157 September 26, 2017 http://www2.eecs.berkeley.edu/Pubs/TechRpts/2017/EECS-2017-157.pdf This paper presents BOOM version 2, an updated version of the Berkeley Out-of-Order Machine. The design exploration was perfo
UC Berkeley Computer Vision Group - Contour Detection and Image Segmentation - Resources
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
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https://www2.eecs.berkeley.edu/Pubs/TechRpts/2014/EECS-2014-130.pdf
Tech Reports | EECS at UC Berkeley
https://www2.eecs.berkeley.edu/Pubs/TechRpts/2013/EECS-2013-58.pdf
MCG: Multiscale Combinatorial Grouping
