(2014) How Good are Detection Proposals, really?
In: Proceedings of the British Machine Vision Conference (BMVC 2014).
Abstract
Current top performing Pascal VOC object detectors employ detection proposals to guide the search for objects thereby avoiding exhaustive sliding window search across images. Despite the popularity of detection proposals, it is unclear which trade-offs are made when using them during object detection. We provide an in depth analysis of ten object proposal methods along with four baselines regarding ground truth annotation recall (on Pascal VOC 2007 and ImageNet 2013), repeatability, and impact on DPM detector performance. Our findings show common weaknesses of existing methods, and provide insights to choose the most adequate method for different settings.
Item Type: | Conference or Workshop Item (A Paper) (Paper) |
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Depositing User: | Sebastian Weisgerber |
Date Deposited: | 22 Feb 2018 11:11 |
Last Modified: | 22 Feb 2018 16:44 |
URI: | https://publications.cispa.saarland/id/eprint/1825 |
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