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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
Enabling Deep Residual Networks for Weakly Supervised Object Detection—0
SLV: Spatial Likelihood Voting for Weakly Supervised Object Detection—0
Adaptive Object Detection with Dual Multi-Label Prediction—0
Learning Object Scale With Click Supervision for Object Detection—0
Weakly Supervised Instance Segmentation by Deep Community Learning—0
Training Object Detectors from Few Weakly-Labeled and Many Unlabeled Images—0
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
WSOD2: Learning Bottom-Up and Top-Down Objectness Distillation for Weakly-Supervised Object DetectionCode0
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