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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
Spatial Likelihood Voting with Self-Knowledge Distillation for Weakly Supervised Object Detection—0
Discovery-and-Selection: Towards Optimal Multiple Instance Learning for Weakly Supervised Object Detection—0
Contrastive Proposal Extension with LSTM Network for Weakly Supervised Object Detection—0
Learning Better Visual Representations for Weakly-Supervised Object Detection Using Natural Language Supervision—0
PGTRNet: Two-phase Weakly Supervised Object Detection with Pseudo Ground Truth Refinement—0
Pseudo-Label Generation-Evaluation Framework For Cross Domain Weakly Supervised Object Detection—0
Multi-patch Feature Pyramid Network for Weakly Supervised Object Detection in Optical Remote Sensing Images—0
CaT: Weakly Supervised Object Detection with Category TransferCode0
Toward Joint Thing-and-Stuff Mining for Weakly Supervised Panoptic Segmentation—0
Informative and Consistent Correspondence Mining for Cross-Domain Weakly Supervised Object Detection—0
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