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Weakly Supervised Object Detection

13 papers with code · Computer Vision
Subtask of Object Detection

Weakly Supervised Object Detection (WSOD) is the task of training object detectors with only image tag supervisions.

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Greatest papers with code

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

PCL: Proposal Cluster Learning for Weakly Supervised Object Detection

9 Jul 2018ppengtang/oicr

The iterative instance classifier refinement is implemented online using multiple streams in convolutional neural networks, where the first is an MIL network and the others are for instance classifier refinement supervised by the preceding one.

MULTIPLE INSTANCE LEARNING OBJECT RECOGNITION WEAKLY SUPERVISED OBJECT DETECTION

Multiple Instance Detection Network with Online Instance Classifier Refinement

CVPR 2017 ppengtang/oicr

We propose a novel online instance classifier refinement algorithm to integrate MIL and the instance classifier refinement procedure into a single deep network, and train the network end-to-end with only image-level supervision, i. e., without object location information.

MULTIPLE INSTANCE LEARNING OBJECT RECOGNITION WEAKLY SUPERVISED OBJECT DETECTION

Weakly Supervised Deep Detection Networks

CVPR 2016 hbilen/WSDDN

Weakly supervised learning of object detection is an important problem in image understanding that still does not have a satisfactory solution.

DATA AUGMENTATION WEAKLY SUPERVISED OBJECT DETECTION

C-MIL: Continuation Multiple Instance Learning for Weakly Supervised Object Detection

CVPR 2019 Winfrand/C-MIL

Weakly supervised object detection (WSOD) is a challenging task when provided with image category supervision but required to simultaneously learn object locations and object detectors.

MULTIPLE INSTANCE LEARNING WEAKLY SUPERVISED OBJECT DETECTION WEAKLY-SUPERVISED OBJECT LOCALIZATION

Min-Entropy Latent Model for Weakly Supervised Object Detection

CVPR 2018 WinFrand/MELM

Weakly supervised object detection is a challenging task when provided with image category supervision but required to learn, at the same time, object locations and object detectors.

IMAGE CLASSIFICATION WEAKLY SUPERVISED OBJECT DETECTION WEAKLY-SUPERVISED OBJECT LOCALIZATION

Self Paced Deep Learning for Weakly Supervised Object Detection

24 May 2016moinnabi/SelfPacedDeepLearning

The main idea is to iteratively select a subset of images and boxes that are the most reliable, and use them for training.

MULTIPLE INSTANCE LEARNING WEAKLY SUPERVISED OBJECT DETECTION

LoANs: Weakly Supervised Object Detection with Localizer Assessor Networks

14 Nov 2018Bartzi/loans

Our student (localizer) is a model that learns to localize an object, the teacher (assessor) assesses the quality of the localization and provides feedback to the student.

WEAKLY SUPERVISED OBJECT DETECTION