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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 111–120 of 142 papers

TitleStatusHype
Spatial Likelihood Voting with Self-Knowledge Distillation for Weakly Supervised Object Detection—0
Tell Me What They're Holding: Weakly-supervised Object Detection with Transferable Knowledge from Human-object Interaction—0
Temporal Dynamic Graph LSTM for Action-driven Video Object Detection—0
Toward Joint Thing-and-Stuff Mining for Weakly Supervised Panoptic Segmentation—0
Towards automatic visual inspection: A weakly supervised learning method for industrial applicable object detection—0
Leveraging Orientation for Weakly Supervised Object Detection with Application to Firearm LocalizationCode0
Min-Entropy Latent Model for Weakly Supervised Object DetectionCode0
C-MIL: Continuation Multiple Instance Learning for Weakly Supervised Object DetectionCode0
WSOD2: Learning Bottom-Up and Top-Down Objectness Distillation for Weakly-Supervised Object DetectionCode0
Cyclic Guidance for Weakly Supervised Joint Detection and SegmentationCode0
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