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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 21–30 of 142 papers

TitleStatusHype
LEOD: Label-Efficient Object Detection for Event CamerasCode1
Cross-Domain Weakly-Supervised Object Detection through Progressive Domain AdaptationCode1
Cyclic-Bootstrap Labeling for Weakly Supervised Object DetectionCode1
Domain-Adaptive Self-Supervised Pre-Training for Face & Body Detection in DrawingsCode1
Object Instance Mining for Weakly Supervised Object DetectionCode1
PCL: Proposal Cluster Learning for Weakly Supervised Object DetectionCode1
Instance-aware, Context-focused, and Memory-efficient Weakly Supervised Object DetectionCode1
Semi-Weakly Supervised Object Detection by Sampling Pseudo Ground-Truth BoxesCode1
Text-image Alignment for Diffusion-based PerceptionCode1
Multiple instance learning on deep features for weakly supervised object detection with extreme domain shiftsCode1
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