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Weakly-Supervised Object Localization

Weakly supervised object localization (WSOL) learns to localize objects with only image-level labels, no object level labels (bonding boxes, etc.,) is needed. It is more attractive since image-level labels are much easier and cheaper to obtain.

Papers

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Showing 101–140 of 140 papers

TitleStatusHype
Weakly Supervised Object Localization Using Things and Stuff Transfer—0
Weakly Supervised Object Localization with Multi-fold Multiple Instance Learning—0
Weakly Supervised Object Localization With Progressive Domain Adaptation—0
Improve CAM with Auto-adapted Segmentation and Co-supervised Augmentation—0
Deep Weakly-Supervised Learning Methods for Classification and Localization in Histology Images: A SurveyCode0
SE3D: A Framework For Saliency Method Evaluation In 3D ImagingCode0
Self-produced Guidance for Weakly-supervised Object LocalizationCode0
DAP: Detection-Aware Pre-training with Weak SupervisionCode0
Causal Explanation of Convolutional Neural NetworksCode0
Weakly Supervised Convolutional LSTM Approach for Tool Tracking in Laparoscopic VideosCode0
Adversarial Complementary Learning for Weakly Supervised Object LocalizationCode0
DANet: Divergent Activation for Weakly Supervised Object LocalizationCode0
Soft Proposal Networks for Weakly Supervised Object LocalizationCode0
Source-Free Domain Adaptation of Weakly-Supervised Object Localization Models for HistologyCode0
Leveraging Transformers for Weakly Supervised Object Localization in Unconstrained VideosCode0
Convolutional STN for Weakly Supervised Object LocalizationCode0
In-sample Contrastive Learning and Consistent Attention for Weakly Supervised Object LocalizationCode0
Min-Entropy Latent Model for Weakly Supervised Object DetectionCode0
WILDCAT: Weakly Supervised Learning of Deep ConvNets for Image Classification, Pointwise Localization and SegmentationCode0
Strengthen Learning Tolerance for Weakly Supervised Object LocalizationCode0
ContextLocNet: Context-Aware Deep Network Models for Weakly Supervised LocalizationCode0
Modularized Textual Grounding for Counterfactual ResilienceCode0
TeD-Loc: Text Distillation for Weakly Supervised Object LocalizationCode0
Combinational Class Activation Maps for Weakly Supervised Object LocalizationCode0
Attention-based Dropout Layer for Weakly Supervised Object LocalizationCode0
Pairwise Similarity Knowledge Transfer for Weakly Supervised Object LocalizationCode0
Background-aware Classification Activation Map for Weakly Supervised Object LocalizationCode0
Hide-and-Seek: Forcing a Network to be Meticulous for Weakly-supervised Object and Action LocalizationCode0
GridMix: Strong regularization through local context mappingCode0
Attributional Robustness Training using Input-Gradient Spatial AlignmentCode0
Knowledge-guided Causal Intervention for Weakly-supervised Object LocalizationCode0
PixelCAM: Pixel Class Activation Mapping for Histology Image Classification and ROI LocalizationCode0
Adversarial Normalization: I Can Visualize Everything (ICE)Code0
Progressive Representation Adaptation for Weakly Supervised Object LocalizationCode0
A Realistic Protocol for Evaluation of Weakly Supervised Object LocalizationCode0
Expeditious Saliency-guided Mix-up through Random Gradient ThresholdingCode0
DiPS: Discriminative Pseudo-Label Sampling with Self-Supervised Transformers for Weakly Supervised Object LocalizationCode0
Rethinking Localization Map: Towards Accurate Object Perception with Self-Enhancement MapsCode0
Rethinking Softmax with Cross-Entropy: Neural Network Classifier as Mutual Information EstimatorCode0
C-MIL: Continuation Multiple Instance Learning for Weakly Supervised Object DetectionCode0
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