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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
Combinational Class Activation Maps for Weakly Supervised Object LocalizationCode0
Adaptively Denoising Proposal Collection for Weakly Supervised Object Localization—0
DANet: Divergent Activation for Weakly Supervised Object LocalizationCode0
Information Entropy Based Feature Pooling for Convolutional Neural Networks—0
Multi-scale discriminative Region Discovery for Weakly-Supervised Object Localization—0
Dual-attention Focused Module for Weakly Supervised Object Localization—0
Weakly Supervised Localization Using Background Images—0
Deep Weakly-Supervised Learning Methods for Classification and Localization in Histology Images: A SurveyCode0
Attention-based Dropout Layer for Weakly Supervised Object LocalizationCode0
Min-max Entropy for Weakly Supervised Pointwise LocalizationCode1
Learning Instance Activation Maps for Weakly Supervised Instance Segmentation—0
Compression and Localization in Reinforcement Learning for ATARI Games—0
C-MIL: Continuation Multiple Instance Learning for Weakly Supervised Object DetectionCode0
Modularized Textual Grounding for Counterfactual ResilienceCode0
Min-Entropy Latent Model for Weakly Supervised Object DetectionCode0
Weakly Supervised Convolutional LSTM Approach for Tool Tracking in Laparoscopic VideosCode0
ML-LocNet: Improving Object Localization with Multi-view Learning Network—0
Self-produced Guidance for Weakly-supervised Object LocalizationCode0
Adversarial Complementary Learning for Weakly Supervised Object LocalizationCode0
Weakly Supervised Object Localization on grocery shelves using simple FCN and Synthetic Dataset—0
Improved Techniques For Weakly-Supervised Object Localization—0
Progressive Representation Adaptation for Weakly Supervised Object LocalizationCode0
Soft Proposal Networks for Weakly Supervised Object LocalizationCode0
Two-Phase Learning for Weakly Supervised Object Localization—0
Object-Extent Pooling for Weakly Supervised Single-Shot Localization—0
WILDCAT: Weakly Supervised Learning of Deep ConvNets for Image Classification, Pointwise Localization and SegmentationCode0
How hard can it be? Estimating the difficulty of visual search in an image—0
Training object class detectors with click supervision—0
Deep Self-Taught Learning for Weakly Supervised Object Localization—0
Hide-and-Seek: Forcing a Network to be Meticulous for Weakly-supervised Object and Action LocalizationCode0
Weakly Supervised Object Localization Using Things and Stuff Transfer—0
ContextLocNet: Context-Aware Deep Network Models for Weakly Supervised LocalizationCode0
Weakly Supervised Object Localization Using Size Estimates—0
Weakly Supervised Object Localization With Progressive Domain Adaptation—0
Improving Weakly-Supervised Object Localization By Micro-Annotation—0
Self-Transfer Learning for Fully Weakly Supervised Object Localization—0
Learning Deep Features for Discriminative LocalizationCode1
Weakly Supervised Object Localization with Multi-fold Multiple Instance Learning—0
Density-Based Region Search with Arbitrary Shape for Object Localization—0
Multi-fold MIL Training for Weakly Supervised Object Localization—0
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