SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 101–110 of 142 papers

TitleStatusHype
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
Weakly Supervised Object Detection in ArtworksCode1
Fewer is More: Image Segmentation Based Weakly Supervised Object Detection with Partial Aggregation—0
Weakly Supervised Region Proposal Network and Object Detection—0
TS2C: Tight Box Mining with Surrounding Segmentation Context for Weakly Supervised Object Detection—0
PCL: Proposal Cluster Learning for Weakly Supervised Object DetectionCode1
Show:102550
← PrevPage 11 of 15Next →

No leaderboard results yet.