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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 76–100 of 142 papers

TitleStatusHype
Towards Precise Weakly Supervised Object Detection via Interactive Contrastive Learning of Context Information—0
Track and Transfer: Watching Videos to Simulate Strong Human Supervision for Weakly-Supervised Object Detection—0
Training Object Detectors from Few Weakly-Labeled and Many Unlabeled Images—0
Transformer-based Multi-Instance Learning for Weakly Supervised Object Detection—0
TS2C: Tight Box Mining with Surrounding Segmentation Context for Weakly Supervised Object Detection—0
Two-phase weakly supervised object detection with pseudo ground truth mining—0
Universal Bounding Box Regression and Its Applications—0
Utilizing the Instability in Weakly Supervised Object Detection—0
W2F: A Weakly-Supervised to Fully-Supervised Framework for Object Detection—0
Weakly Supervised Cascaded Convolutional Networks—0
Weakly Supervised Instance Segmentation by Deep Community Learning—0
Weakly-supervised Learning of Mid-level Features for Pedestrian Attribute Recognition and Localization—0
Weakly Supervised Localization using Deep Feature Maps—0
Weakly supervised object detection using pseudo-strong labels—0
Weakly Supervised Object Detection with Pointwise Mutual Information—0
Weakly Supervised Object Detection With Convex Clustering—0
Weakly Supervised Object Detection with Segmentation Collaboration—0
Weakly Supervised Object Detection with 2D and 3D Regression Neural Networks—0
Weakly Supervised Object Discovery by Generative Adversarial & Ranking Networks—0
Weakly Supervised Open-Vocabulary Object Detection—0
Weakly Supervised Region Proposal Network and Object Detection—0
WSOD2: Learning Bottom-up and Top-down Objectness Distillation forWeakly-supervised Object Detection—0
WSOD with PSNet and Box Regression—0
You Reap What You Sow: Using Videos to Generate High Precision Object Proposals for Weakly-Supervised Object Detection—0
Zigzag Learning for Weakly Supervised Object Detection—0
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