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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 91–100 of 142 papers

TitleStatusHype
C-MIDN: Coupled Multiple Instance Detection Network With Segmentation Guidance for Weakly Supervised Object Detection—0
Towards Object Detection from Motion—0
WSOD^2: Learning Bottom-up and Top-down Objectness Distillation for Weakly-supervised Object DetectionCode0
WSOD2: Learning Bottom-up and Top-down Objectness Distillation forWeakly-supervised Object Detection—0
Object-Aware Instance Labeling for Weakly Supervised Object Detection—0
Utilizing the Instability in Weakly Supervised Object Detection—0
Weakly Supervised Object Detection with 2D and 3D Regression Neural Networks—0
Cyclic Guidance for Weakly Supervised Joint Detection and SegmentationCode0
You Reap What You Sow: Using Videos to Generate High Precision Object Proposals for Weakly-Supervised Object Detection—0
Leveraging Orientation for Weakly Supervised Object Detection with Application to Firearm LocalizationCode0
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