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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 71–80 of 142 papers

TitleStatusHype
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
Towards Computational Baby Learning: A Weakly-Supervised Approach for Object Detection—0
Towards Object Detection from Motion—0
Towards Precise Weakly Supervised Object Detection via Interactive Contrastive Learning of Context Information—0
Track and Transfer: Watching Videos to Simulate Strong Human Supervision for Weakly-Supervised Object Detection—0
Training Object Detectors from Few Weakly-Labeled and Many Unlabeled Images—0
Transformer-based Multi-Instance Learning for Weakly Supervised Object Detection—0
TS2C: Tight Box Mining with Surrounding Segmentation Context for Weakly Supervised Object Detection—0
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