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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 51–60 of 142 papers

TitleStatusHype
Towards Precise Weakly Supervised Object Detection via Interactive Contrastive Learning of Context Information—0
DETR with Additional Global Aggregation for Cross-domain Weakly Supervised Object Detection—0
Transformer-based Multi-Instance Learning for Weakly Supervised Object Detection—0
Boosting Weakly Supervised Object Detection using Fusion and Priors from Hallucinated Depth—0
VEIL: Vetting Extracted Image Labels from In-the-Wild Captions for Weakly-Supervised Object DetectionCode0
D2DF2WOD: Learning Object Proposals for Weakly-Supervised Object Detection via Progressive Domain Adaptation—0
SESS: Saliency Enhancing with Scaling and SlidingCode0
Online progressive instance-balanced sampling for weakly supervised object detection—0
Compositional Mixture Representations for Vision and Text—0
Absolute Wrong Makes Better: Boosting Weakly Supervised Object Detection via Negative Deterministic Information—0
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