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Weakly-Supervised Object Localization

Weakly supervised object localization (WSOL) learns to localize objects with only image-level labels, no object level labels (bonding boxes, etc.,) is needed. It is more attractive since image-level labels are much easier and cheaper to obtain.

Papers

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Showing 121–130 of 140 papers

TitleStatusHype
Weakly Supervised Object Localization on grocery shelves using simple FCN and Synthetic Dataset—0
Improved Techniques For Weakly-Supervised Object Localization—0
Progressive Representation Adaptation for Weakly Supervised Object LocalizationCode0
Soft Proposal Networks for Weakly Supervised Object LocalizationCode0
Two-Phase Learning for Weakly Supervised Object Localization—0
Object-Extent Pooling for Weakly Supervised Single-Shot Localization—0
WILDCAT: Weakly Supervised Learning of Deep ConvNets for Image Classification, Pointwise Localization and SegmentationCode0
How hard can it be? Estimating the difficulty of visual search in an image—0
Training object class detectors with click supervision—0
Deep Self-Taught Learning for Weakly Supervised Object Localization—0
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