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Object Localization

41 papers with code · Computer Vision

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Grid R-CNN

CVPR 2019 open-mmlab/mmdetection

This paper proposes a novel object detection framework named Grid R-CNN, which adopts a grid guided localization mechanism for accurate object detection.

#16 best model for Object Detection on COCO

OBJECT DETECTION OBJECT LOCALIZATION

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.

OBJECT LOCALIZATION

VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection

CVPR 2018 charlesq34/pointnet

Accurate detection of objects in 3D point clouds is a central problem in many applications, such as autonomous navigation, housekeeping robots, and augmented/virtual reality.

3D OBJECT DETECTION AUTONOMOUS NAVIGATION FEATURE ENGINEERING OBJECT LOCALIZATION

Dilated Residual Networks

CVPR 2017 osmr/imgclsmob

Convolutional networks for image classification progressively reduce resolution until the image is represented by tiny feature maps in which the spatial structure of the scene is no longer discernible.

IMAGE CLASSIFICATION OBJECT LOCALIZATION SCENE UNDERSTANDING SEMANTIC SEGMENTATION

Bounding Box Regression with Uncertainty for Accurate Object Detection

CVPR 2019 yihui-he/KL-Loss

Large-scale object detection datasets (e. g., MS-COCO) try to define the ground truth bounding boxes as clear as possible.

OBJECT DETECTION OBJECT LOCALIZATION

Microsoft COCO: Common Objects in Context

1 May 2014nightrome/cocostuff10k

We present a new dataset with the goal of advancing the state-of-the-art in object recognition by placing the question of object recognition in the context of the broader question of scene understanding.

INSTANCE SEGMENTATION OBJECT LOCALIZATION OBJECT RECOGNITION SCENE UNDERSTANDING SEMANTIC SEGMENTATION

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

LocNet: Improving Localization Accuracy for Object Detection

CVPR 2016 gidariss/locnet

We propose a novel object localization methodology with the purpose of boosting the localization accuracy of state-of-the-art object detection systems.

OBJECT DETECTION OBJECT LOCALIZATION

Transfer learning for time series classification

5 Nov 2018hfawaz/bigdata18

Transfer learning for deep neural networks is the process of first training a base network on a source dataset, and then transferring the learned features (the network's weights) to a second network to be trained on a target dataset.

OBJECT LOCALIZATION TIME SERIES TIME SERIES CLASSIFICATION TRANSFER LEARNING