Title: Recovering Hard-to-Find Object Instances by Sampling Context-based Object Proposals
Authors: Oramas Mogrovejo, José Antonio ×
Tuytelaars, Tinne #
Issue Date: 18-Aug-2016
Publisher: Academic Press
Series Title: Computer Vision and Image Understanding
Abstract: In this paper we focus on improving object detection performance in terms of recall. We propose a post-detection stage during which we explore the image with the objective of recovering missed detections. This exploration is performed by sampling object proposals in the image. We analyze four different strategies to perform this sampling, giving special attention to strategies that exploit spatial relations between objects. In addition, we propose a novel method to discover higher-order relations between groups of objects. Experiments on the challenging KITTI dataset show that our proposed relations-based proposal generation strategies can help improving recall at the cost of a relatively low amount of object proposals.
Description: Oramas Mogrovejo J.A., Tuytelaars T., ''Recovering hard-to-find object instances by sampling context-based object proposals'', Computer vision and image understanding, 2016 (Available online 18 August 2016) (accepted).
ISSN: 1077-3142
Publication status: accepted
KU Leuven publication type: IT
Appears in Collections:ESAT - PSI, Processing Speech and Images
× corresponding author
# (joint) last author

Files in This Item:
File Description Status SizeFormat
oramas_tuytelaars-contextBasedProposals-cviu16_authorVersion.pdfThis is the author’s version of an article accepted for publication. Changes were made to this version by the publisher prior to publication. The final version of record is available at: Accepted 6744KbAdobe PDFView/Open Request a copy

These files are only available to some KU Leuven Association staff members


All items in Lirias are protected by copyright, with all rights reserved.