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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 111–120 of 142 papers

TitleStatusHype
Learning Object Scale With Click Supervision for Object Detection—0
Multi-Evidence Filtering and Fusion for Multi-Label Classification, Object Detection and Semantic Segmentation Based on Weakly Supervised Learning—0
Multi-patch Feature Pyramid Network for Weakly Supervised Object Detection in Optical Remote Sensing Images—0
Multiple Instance Curriculum Learning for Weakly Supervised Object Detection—0
Negative Prototypes Guided Contrastive Learning for WSOD—0
NOTE-RCNN: NOise Tolerant Ensemble RCNN for Semi-Supervised Object Detection—0
Object-Aware Instance Labeling for Weakly Supervised Object Detection—0
On learning to localize objects with minimal supervision—0
Online Active Proposal Set Generation for Weakly Supervised Object Detection—0
Online progressive instance-balanced sampling for weakly supervised object detection—0
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