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Weakly Supervised Object Detection

Weakly Supervised Object Detection (WSOD) is the task of training object detectors with only image tag supervisions.

( Image credit: Soft Proposal Networks for Weakly Supervised Object Localization )

Papers

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Showing 81–90 of 142 papers

TitleStatusHype
Training Object Detectors from Few Weakly-Labeled and Many Unlabeled Images—0
Towards Precise End-to-end Weakly Supervised Object Detection NetworkCode1
WSOD with PSNet and Box Regression—0
Tell Me What They're Holding: Weakly-supervised Object Detection with Transferable Knowledge from Human-object Interaction—0
Adaptively Denoising Proposal Collection forWeakly Supervised Object Localization—0
C-MIDN: Coupled Multiple Instance Detection Network With Segmentation Guidance for Weakly Supervised Object Detection—0
WSOD2: Learning Bottom-Up and Top-Down Objectness Distillation for Weakly-Supervised Object DetectionCode0
Towards Object Detection from Motion—0
WSOD2: Learning Bottom-up and Top-down Objectness Distillation forWeakly-supervised Object Detection—0
WSOD^2: Learning Bottom-up and Top-down Objectness Distillation for Weakly-supervised Object DetectionCode0
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