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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 101–142 of 142 papers

TitleStatusHype
Weakly Supervised Complementary Parts Models for Fine-Grained Image Classification from the Bottom UpCode0
Min-Entropy Latent Model for Weakly Supervised Object DetectionCode0
NOTE-RCNN: NOise Tolerant Ensemble RCNN for Semi-Supervised Object Detection—0
Dissimilarity Coefficient based Weakly Supervised Object Detection—0
LoANs: Weakly Supervised Object Detection with Localizer Assessor NetworksCode0
Weakly Supervised Object Detection in ArtworksCode1
Fewer is More: Image Segmentation Based Weakly Supervised Object Detection with Partial Aggregation—0
Weakly Supervised Region Proposal Network and Object Detection—0
TS2C: Tight Box Mining with Surrounding Segmentation Context for Weakly Supervised Object Detection—0
PCL: Proposal Cluster Learning for Weakly Supervised Object DetectionCode1
Generative Adversarial Learning Towards Fast Weakly Supervised Detection—0
W2F: A Weakly-Supervised to Fully-Supervised Framework for Object Detection—0
Zigzag Learning for Weakly Supervised Object Detection—0
Cross-Domain Weakly-Supervised Object Detection through Progressive Domain AdaptationCode1
Multi-Evidence Filtering and Fusion for Multi-Label Classification, Object Detection and Semantic Segmentation Based on Weakly Supervised Learning—0
Collaborative Learning for Weakly Supervised Object Detection—0
Weakly Supervised Object Detection with Pointwise Mutual Information—0
Multiple Instance Curriculum Learning for Weakly Supervised Object Detection—0
Weakly Supervised Object Discovery by Generative Adversarial & Ranking Networks—0
Soft Proposal Networks for Weakly Supervised Object LocalizationCode0
PPR-FCN: Weakly Supervised Visual Relation Detection via Parallel Pairwise R-FCN—0
Optimizing Region Selection for Weakly Supervised Object Detection—0
Temporal Dynamic Graph LSTM for Action-driven Video Object Detection—0
Exploiting Web Images for Weakly Supervised Object Detection—0
Variational Bayesian Multiple Instance Learning With Gaussian ProcessesCode0
WILDCAT: Weakly Supervised Learning of Deep ConvNets for Image Classification, Pointwise Localization and SegmentationCode0
Saliency Guided End-to-End Learning for Weakly Supervised Object Detection—0
Deep Self-Taught Learning for Weakly Supervised Object Localization—0
Multiple Instance Detection Network with Online Instance Classifier RefinementCode1
Bridging Saliency Detection to Weakly Supervised Object Detection Based on Self-paced Curriculum Learning—0
Weakly Supervised Cascaded Convolutional Networks—0
Weakly-supervised Learning of Mid-level Features for Pedestrian Attribute Recognition and Localization—0
ContextLocNet: Context-Aware Deep Network Models for Weakly Supervised LocalizationCode0
Weakly supervised object detection using pseudo-strong labels—0
Self Paced Deep Learning for Weakly Supervised Object DetectionCode0
Track and Transfer: Watching Videos to Simulate Strong Human Supervision for Weakly-Supervised Object Detection—0
Weakly Supervised Localization using Deep Feature Maps—0
Towards Computational Baby Learning: A Weakly-Supervised Approach for Object Detection—0
ProNet: Learning to Propose Object-specific Boxes for Cascaded Neural Networks—0
Weakly Supervised Deep Detection NetworksCode0
Weakly Supervised Object Detection With Convex Clustering—0
On learning to localize objects with minimal supervision—0
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