Category Independent Object Proposals

Overview

This work aims to provide a small pool of regions for an image, that are likely to contain every object in the image, regardless of category.

01/13/2014 - An expanded version of this work will appear in the February 2014 volume of PAMI. Please cite this version [pdf]
11/23/2010 - Precomputed proposals for Pascal VOC 2010 + Support for 64-bit Windows
9/21/2010 - Included support for 32-bit linux
9/20/2010 - The website is now up!: The code to generate proposals for an image is now available.

Category Independent Object Proposal Code PROP_code.tar.gz (15MB): The code to generate a ranked pool of candidate object regions for each image.; This code is written in Matlab, with supporing compiled mex functions.; I've tested it on 32 and 64 bit linux machines (Matlab 2009b i.e. 7.9)
Annotated Dataset PROP_BSDS_ann.tar.gz (390KB): These are the annotations we added to the Berkeley Segmentation Dataset.; These annotations provide the segmentations for each object, and respect the region boundaries of the original dataset.
PASCAL VOC 2010 Precomputed Proposals pascal_2010_proposals.tar.gz (15.6GB!): Precomputed regions for each image in PASCAL VOC 2010 (train+val+test). Please note that this is a very large file.

This research is supported by NSF IIS-0904209: Physically Grounded Object Recognition.

Please contact iendres2 -at- uiuc.edu with any questions.

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