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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
Universal Bounding Box Regression and Its Applications—0
C-MIL: Continuation Multiple Instance Learning for Weakly Supervised Object DetectionCode0
Activity Driven Weakly Supervised Object Detection—0
Weakly Supervised Object Detection with Segmentation Collaboration—0
Weakly Supervised Complementary Parts Models for Fine-Grained Image Classification from the Bottom UpCode0
Min-Entropy Latent Model for Weakly Supervised Object DetectionCode0
NOTE-RCNN: NOise Tolerant Ensemble RCNN for Semi-Supervised Object Detection—0
Dissimilarity Coefficient based Weakly Supervised Object Detection—0
LoANs: Weakly Supervised Object Detection with Localizer Assessor NetworksCode0
Fewer is More: Image Segmentation Based Weakly Supervised Object Detection with Partial Aggregation—0
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