Soft Sampling for Robust Object Detection

Gradient-based learning applied to document recognition

Yann LeCun, Léon Bottou, Yoshua Bengio, and Patrick Haffner · 1998

Earlier work this paper cites.

Semi-supervised self-training of object detection models

Chuck Rosenberg, Martial Hebert, and Henry Schneiderman · 2005

Earlier work this paper cites.

Imagenet: A large-scale hierarchical image database

Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009

Earlier work this paper cites.

The pascal visual object classes (voc) challenge

M. Everingham, L. Van Gool, C. K. I. Williams, J. Winn, and A. Zisserman · 2010

Earlier work this paper cites.

Object detection with discriminatively trained part-based models

Pedro F Felzenszwalb, Ross B Girshick, David McAllester, and Deva Ramanan · 2010

Earlier work this paper cites.

Fast, accurate detection of 100,000 object classes on a single machine

Thomas Dean, Mark A Ruzon, Mark Segal, Jonathon Shlens, Sudheendra Vijayanarasimhan, and Jay Yagnik · 2013

Earlier work this paper cites.

Microsoft coco: Common objects in context

Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick · 2014

Earlier work this paper cites.

Very deep convolutional networks for large-scale image recognition

Original

Karen Simonyan and Andrew Zisserman · 2014

Earlier work this paper cites.

Faster r-cnn: Towards real-time object detection with region proposal networks

Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun · 2015

Earlier work this paper cites.

R-fcn: Object detection via region-based fully convolutional networks

Jifeng Dai, Yi Li, Kaiming He, and Jian Sun · 2016

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Deep residual learning for image recognition

Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016

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Training region-based object detectors with online hard example mining

Abhinav Shrivastava, Abhinav Gupta, and Ross Girshick · 2016

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Large scale semi-supervised object detection using visual and semantic knowledge transfer

Yuxing Tang, Josiah Wang, Boyang Gao, Emmanuel Dellandréa, Robert Gaizauskas, and Liming Chen · 2016

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Soft-nms - improving object detection with one line of code

Navaneeth Bodla, Bharat Singh, Rama Chellappa, and Larry S Davis · 2017

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Deformable convolutional networks

Jifeng Dai, Haozhi Qi, Yuwen Xiong, Yi Li, Guodong Zhang, Han Hu, and Yichen Wei · 2017

Aggregated residual transformations for deep neural networks

Saining Xie, Ross Girshick, Piotr Dollár, Zhuowen Tu, and Kaiming He · 2017

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Understanding deep learning requires rethinking generalization

Chiyuan Zhang, Samy Bengio, Moritz Hardt, Benjamin Recht, and Oriol Vinyals · 2017

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Solution for large-scale hierarchical object detection datasets with incomplete annotation and data imbalance

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Yuan Gao, Xingyuan Bu, Yang Hu, Hui Shen, Ti Bai, Xubin Li, and Shilei Wen · 2018

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The open images dataset v4: Unified image classification, object detection, and visual relationship detection at scale

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Alina Kuznetsova, Hassan Rom, Neil Alldrin, Jasper Uijlings, Ivan Krasin, Jordi Pont-Tuset, Shahab Kamali, Stefan Popov, Matteo Malloci, Tom Duerig, et al · 2018

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Focal loss for dense object detection

Tsung-Yi Lin, Priyal Goyal, Ross Girshick, Kaiming He, and Piotr Dollár · 2018