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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 81–90 of 142 papers

TitleStatusHype
You Reap What You Sow: Using Videos to Generate High Precision Object Proposals for Weakly-Supervised Object Detection—0
Absolute Wrong Makes Better: Boosting Weakly Supervised Object Detection via Negative Deterministic Information—0
Zigzag Learning for Weakly Supervised Object Detection—0
Activity Driven Weakly Supervised Object Detection—0
Adaptively Denoising Proposal Collection forWeakly Supervised Object Localization—0
Adaptive Object Detection with Dual Multi-Label Prediction—0
Boosting Weakly Supervised Object Detection using Fusion and Priors from Hallucinated Depth—0
Bridging Saliency Detection to Weakly Supervised Object Detection Based on Self-paced Curriculum Learning—0
Cascade Attentive Dropout for Weakly Supervised Object Detection—0
Class Agnostic Instance-level Descriptor for Visual Instance Search—0
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