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» Learning Object Shape: From Drawings to Images
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PAMI
2008
250views more  PAMI 2008»
14 years 10 months ago
Combined Top-Down/Bottom-Up Segmentation
We construct an image segmentation scheme that combines top-down (TD) with bottom-up (BU) processing. In the proposed scheme, segmentation and recognition are intertwined rather th...
Eran Borenstein, Shimon Ullman
ECCV
2010
Springer
14 years 8 months ago
Non-local Characterization of Scenery Images: Statistics, 3D Reasoning, and a Generative Model
Abstract. This work focuses on characterizing scenery images. We semantically divide the objects in natural landscape scenes into background and foreground and show that the shapes...
Tamar Avraham, Michael Lindenbaum
ECCV
2008
Springer
15 years 11 months ago
Saliency Based Opportunistic Search for Object Part Extraction and Labeling
We study the task of object part extraction and labeling, which seeks to understand objects beyond simply identifiying their bounding boxes. We start from bottom-up segmentation of...
Yang Wu, Qihui Zhu, Jianbo Shi, Nanning Zheng
CVPR
2005
IEEE
15 years 12 months ago
A Sparse Object Category Model for Efficient Learning and Exhaustive Recognition
We present a "parts and structure" model for object category recognition that can be learnt efficiently and in a semisupervised manner: the model is learnt from example ...
Robert Fergus, Pietro Perona, Andrew Zisserman
IROS
2008
IEEE
238views Robotics» more  IROS 2008»
15 years 4 months ago
Shape-guided superpixel grouping for trail detection and tracking
Abstract— We describe a framework for detecting and tracking continuous ”trails” in images and image sequences for autonomous robot navigation. Continuous trails are extended...
Christopher Rasmussen, Donald Scott