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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 61–70 of 142 papers

TitleStatusHype
Negative Prototypes Guided Contrastive Learning for WSOD—0
Multiple Instance Curriculum Learning for Weakly Supervised Object Detection—0
Discovery-and-Selection: Towards Optimal Multiple Instance Learning for Weakly Supervised Object Detection—0
Multi-patch Feature Pyramid Network for Weakly Supervised Object Detection in Optical Remote Sensing Images—0
Multi-Evidence Filtering and Fusion for Multi-Label Classification, Object Detection and Semantic Segmentation Based on Weakly Supervised Learning—0
DETR with Additional Global Aggregation for Cross-domain Weakly Supervised Object Detection—0
Deep Self-Taught Learning for Weakly Supervised Object Localization—0
Class Agnostic Instance-level Descriptor for Visual Instance Search—0
Deep Learning for Weakly-Supervised Object Detection and Object Localization: A Survey—0
Learning Object Scale With Click Supervision for Object Detection—0
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