Weakly Supervised Object Detection

26 papers with code • 15 benchmarks • 9 datasets

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 )

Greatest papers with code

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

durandtibo/wildcat.pytorch CVPR 2017

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

General Classification Image Classification +3

Soft Proposal Networks for Weakly Supervised Object Localization

yeezhu/SPN.pytorch ICCV 2017

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

ppengtang/oicr 9 Jul 2018

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 +1

Multiple Instance Detection Network with Online Instance Classifier Refinement

ppengtang/oicr CVPR 2017

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 +1

Towards Precise End-to-end Weakly Supervised Object Detection Network

ppengtang/pcl.pytorch ICCV 2019

It is challenging for weakly supervised object detection network to precisely predict the positions of the objects, since there are no instance-level category annotations.

Multiple Instance Learning Weakly Supervised Object Detection

Weakly Supervised Deep Detection Networks

hbilen/WSDDN CVPR 2016

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

Data Augmentation General Classification +1

Harmonizing Transferability and Discriminability for Adapting Object Detectors

chaoqichen/HTCN CVPR 2020

Recent advances in adaptive object detection have achieved compelling results in virtue of adversarial feature adaptation to mitigate the distributional shifts along the detection pipeline.

Weakly Supervised Object Detection