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ECCV
2008
Springer
16 years 8 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
ICCV
2011
IEEE
14 years 6 months ago
Adaptive Deconvolutional Networks for Mid and High Level Feature Learning
We present a hierarchical model that learns image decompositions via alternating layers of convolutional sparse coding and max pooling. When trained on natural images, the layers ...
Matthew D. Zeiler, Graham W. Taylor, Rob Fergus
TIP
2010
205views more  TIP 2010»
15 years 1 months ago
Variational Region-Based Segmentation Using Multiple Texture Statistics
This paper addresses variational supervised texture segmentation. The main contributions are twofold. First, the proposed method circumvents a major problem related to classical t...
Imen Karoui, Ronan Fablet, Jean-Marc Boucher, Jean...
WWW
2011
ACM
15 years 1 months ago
Learning to re-rank: query-dependent image re-ranking using click data
Our objective is to improve the performance of keyword based image search engines by re-ranking their baseline results. To this end, we address three limitations of existing searc...
Vidit Jain, Manik Varma
CHI
2009
ACM
16 years 7 months ago
Learning to predict information needs: context-aware display as a cognitive aid and an assessment tool
We discuss the problem of assessing and aiding user performance in dynamic tasks that require rapid selection among multiple information sources. Motivated by research in human se...
Bradley C. Love, Matt Jones, Marc T. Tomlinson, Mi...