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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 101–110 of 142 papers

TitleStatusHype
PGTRNet: Two-phase Weakly Supervised Object Detection with Pseudo Ground Truth Refinement—0
PPR-FCN: Weakly Supervised Visual Relation Detection via Parallel Pairwise R-FCN—0
ProNet: Learning to Propose Object-specific Boxes for Cascaded Neural Networks—0
Pseudo-Label Generation-Evaluation Framework For Cross Domain Weakly Supervised Object Detection—0
Read, look and detect: Bounding box annotation from image-caption pairs—0
Saliency Guided End-to-End Learning for Weakly Supervised Object Detection—0
Salvage of Supervision in Weakly Supervised Object Detection—0
Self-Classification Enhancement and Correction for Weakly Supervised Object Detection—0
Self-supervised object detection from audio-visual correspondence—0
SLV: Spatial Likelihood Voting for Weakly Supervised Object Detection—0
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