Browse SoTA > Computer Vision > Object Localization > Weakly-Supervised Object Localization

Weakly-Supervised Object Localization

18 papers with code · Computer Vision
Subtask of Object Localization

Leaderboards

Greatest papers with code

Learning Deep Features for Discriminative Localization

CVPR 2016 tensorpack/tensorpack

In this work, we revisit the global average pooling layer proposed in [13], and shed light on how it explicitly enables the convolutional neural network to have remarkable localization ability despite being trained on image-level labels.

WEAKLY-SUPERVISED OBJECT LOCALIZATION

WILDCAT: Weakly Supervised Learning of Deep ConvNets for Image Classification, Pointwise Localization and Segmentation

CVPR 2017 durandtibo/wildcat.pytorch

This paper introduces WILDCAT, a deep learning method which jointly aims at aligning image regions for gaining spatial invariance and learning strongly localized features.

IMAGE CLASSIFICATION SEMANTIC SEGMENTATION WEAKLY-SUPERVISED OBJECT LOCALIZATION

Soft Proposal Networks for Weakly Supervised Object Localization

ICCV 2017 yeezhu/SPN.pytorch

Weakly supervised object localization remains challenging, where only image labels instead of bounding boxes are available during training.

WEAKLY SUPERVISED OBJECT DETECTION WEAKLY-SUPERVISED OBJECT LOCALIZATION

Evaluation for Weakly Supervised Object Localization: Protocol, Metrics, and Datasets

8 Jul 2020clovaai/wsolevaluation

In this paper, we argue that WSOL task is ill-posed with only image-level labels, and propose a new evaluation protocol where full supervision is limited to only a small held-out set not overlapping with the test set.

FEW-SHOT LEARNING MODEL SELECTION WEAKLY-SUPERVISED OBJECT LOCALIZATION

Evaluating Weakly Supervised Object Localization Methods Right

CVPR 2020 clovaai/wsolevaluation

In this paper, we argue that WSOL task is ill-posed with only image-level labels, and propose a new evaluation protocol where full supervision is limited to only a small held-out set not overlapping with the test set.

FEW-SHOT LEARNING MODEL SELECTION WEAKLY-SUPERVISED OBJECT LOCALIZATION

Attention-based Dropout Layer for Weakly Supervised Object Localization

CVPR 2019 junsukchoe/ADL

Weakly Supervised Object Localization (WSOL) techniques learn the object location only using image-level labels, without location annotations.

WEAKLY-SUPERVISED OBJECT LOCALIZATION

Attention-Based Dropout Layer for Weakly Supervised Object Localization

CVPR 2019 junsukchoe/ADL

Weakly Supervised Object Localization (WSOL) techniques learn the object location only using image-level labels, without location annotations.

WEAKLY-SUPERVISED OBJECT LOCALIZATION

Rethinking Softmax with Cross-Entropy: Neural Network Classifier as Mutual Information Estimator

25 Nov 2019ZhenyueQin/Research-Softmax-with-Mutual-Information

We show that optimising the parameters of classification neural networks with softmax cross-entropy is equivalent to maximising the mutual information between inputs and labels under the balanced data assumption.

FINE-GRAINED IMAGE CLASSIFICATION WEAKLY-SUPERVISED OBJECT LOCALIZATION