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A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics
This paper presents a database containing 'ground truth' segmentations produced by humans for images of a wide variety of natural scenes. We define an error measure which quantifies the consistencyExpand
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Learning to detect natural image boundaries using local brightness, color, and texture cues
The goal of this work is to accurately detect and localize boundaries in natural scenes using local image measurements. We formulate features that respond to characteristic changes in brightness,Expand
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Spectral grouping using the Nystrom method
Spectral graph theoretic methods have recently shown great promise for the problem of image segmentation. However, due to the computational demands of these approaches, applications to large problemsExpand
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Globally-optimal greedy algorithms for tracking a variable number of objects
We analyze the computational problem of multi-object tracking in video sequences. We formulate the problem using a cost function that requires estimating the number of tracks, as well as their birthExpand
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Photo Aesthetics Ranking Network with Attributes and Content Adaptation
Real-world applications could benefit from the ability to automatically generate a fine-grained ranking of photo aesthetics. However, previous methods for image aesthetics analysis have primarilyExpand
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From contours to regions: An empirical evaluation
We propose a generic grouping algorithm that constructs a hierarchy of regions from the output of any contour detector. Our method consists of two steps, an oriented watershed transform (OWT) to formExpand
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Using contours to detect and localize junctions in natural images
Contours and junctions are important cues for perceptual organization and shape recognition. Detecting junctions locally has proved problematic because the image intensity surface is confusing in theExpand
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Discriminative models for multi-class object layout
Many state-of-the-art approaches for object recognition reduce the problem to a 0-1 classification task. This allows one to leverage sophisticated machine learning techniques for training classifiersExpand
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From contours to regions: An empirical evaluation
We propose a generic grouping algorithm that constructs a hierarchy of regions from the output of any contour detector. Our method consists of two steps, an oriented watershed transform (OWT) to formExpand
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Multiresolution Models for Object Detection
Most current approaches to recognition aim to be scale-invariant. However, the cues available for recognizing a 300 pixel tall object are qualitatively different from those for recognizing a 3 pixelExpand
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