Article

Finding Things: Image Parsing with Regions and Per-Exemplar Detectors

Authors:

Joseph Tighe,

Svetlana LazebnikAuthors Info & Claims

CVPR '13: Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition

Pages 3001 - 3008

https://doi.org/10.1109/CVPR.2013.386

Published: 23 June 2013 Publication History

Abstract

This paper presents a system for image parsing, or labeling each pixel in an image with its semantic category, aimed at achieving broad coverage across hundreds of object categories, many of them sparsely sampled. The system combines region-level features with per-exemplar sliding window detectors. Per-exemplar detectors are better suited for our parsing task than traditional bounding box detectors: they perform well on classes with little training data and high intra-class variation, and they allow object masks to be transferred into the test image for pixel-level segmentation. The proposed system achieves state-of-the-art accuracy on three challenging datasets, the largest of which contains 45,676 images and 232 labels.

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Zhou QYang WGao GOu WLu HChen JLatecki L(2019)Multi-scale deep context convolutional neural networks for semantic segmentationWorld Wide Web10.1007/s11280-018-0556-322:2(555-570)Online publication date: 1-Mar-2019
https://dl.acm.org/doi/10.1007/s11280-018-0556-3
Nguyen TLiu L(2017)Salient object detection with semantic priorsProceedings of the 26th International Joint Conference on Artificial Intelligence10.5555/3171837.3171916(4499-4505)Online publication date: 19-Aug-2017
https://dl.acm.org/doi/10.5555/3171837.3171916
Shelhamer ELong JDarrell T(2017)Fully Convolutional Networks for Semantic SegmentationIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2016.257268339:4(640-651)Online publication date: 1-Apr-2017
https://dl.acm.org/doi/10.1109/TPAMI.2016.2572683
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Published In

CVPR '13: Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition

June 2013

3752 pages

ISBN:9780769549897

Publisher

IEEE Computer Society

United States

Publication History

Published: 23 June 2013

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Zhou QYang WGao GOu WLu HChen JLatecki L(2019)Multi-scale deep context convolutional neural networks for semantic segmentationWorld Wide Web10.1007/s11280-018-0556-322:2(555-570)Online publication date: 1-Mar-2019
https://dl.acm.org/doi/10.1007/s11280-018-0556-3
Nguyen TLiu L(2017)Salient object detection with semantic priorsProceedings of the 26th International Joint Conference on Artificial Intelligence10.5555/3171837.3171916(4499-4505)Online publication date: 19-Aug-2017
https://dl.acm.org/doi/10.5555/3171837.3171916
Shelhamer ELong JDarrell T(2017)Fully Convolutional Networks for Semantic SegmentationIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2016.257268339:4(640-651)Online publication date: 1-Apr-2017
https://dl.acm.org/doi/10.1109/TPAMI.2016.2572683
Lu ZFu ZXiang THan PWang LGao X(2017)Learning from Weak and Noisy Labels for Semantic SegmentationIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2016.255217239:3(486-500)Online publication date: 1-Mar-2017
https://dl.acm.org/doi/10.1109/TPAMI.2016.2552172
Cheng FHe XZhang H(2017)Stacked Learning to Search for Scene LabelingIEEE Transactions on Image Processing10.1109/TIP.2017.266821826:4(1887-1898)Online publication date: 1-Apr-2017
https://dl.acm.org/doi/10.1109/TIP.2017.2668218
Becattini FSeidenari LBimbo A(2017)Indexing quantized ensembles of exemplar-SVMs with rejecting taxonomiesMultimedia Tools and Applications10.1007/s11042-017-4794-776:21(22647-22668)Online publication date: 1-Nov-2017
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(2016)Label transfer via sparse representationPattern Recognition Letters10.1016/j.patrec.2015.11.00970:C(1-7)Online publication date: 15-Jan-2016
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(2016)Automatic non-parametric image parsing via hierarchical semantic voting based on sparse-dense reconstruction and spatial-contextual cuesNeurocomputing10.1016/j.neucom.2016.03.034201:C(92-103)Online publication date: 12-Aug-2016
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(2016)Semantic labeling for prosthetic visionComputer Vision and Image Understanding10.1016/j.cviu.2016.02.015149:C(113-125)Online publication date: 1-Aug-2016
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Li XMou LLu X(2016)Video parsing via spatiotemporally analysis with imagesMultimedia Tools and Applications10.1007/s11042-015-2735-x75:19(11961-11976)Online publication date: 1-Oct-2016
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