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Robust Object Detection in Remote Sensing Imagery with Noisy and Sparse
  Geo-Annotations (Full Version)

Robust Object Detection in Remote Sensing Imagery with Noisy and Sparse Geo-Annotations (Full Version)

24 October 2022
Maximilian Bernhard
Matthias Schubert
    ObjD
ArXivPDFHTML

Papers citing "Robust Object Detection in Remote Sensing Imagery with Noisy and Sparse Geo-Annotations (Full Version)"

34 / 34 papers shown
Title
SparseDet: Improving Sparsely Annotated Object Detection with
  Pseudo-positive Mining
SparseDet: Improving Sparsely Annotated Object Detection with Pseudo-positive Mining
Saksham Suri
Sai Saketh Rambhatla
Rama Chellappa
Abhinav Shrivastava
ObjD
55
11
0
12 Jan 2022
Bootstrap Your Object Detector via Mixed Training
Bootstrap Your Object Detector via Mixed Training
Mengde Xu
Zheng Zhang
Fangyun Wei
Yutong Lin
Yue Cao
Stephen Lin
Han Hu
Xiang Bai
ObjD
71
6
0
04 Nov 2021
Alpha-IoU: A Family of Power Intersection over Union Losses for Bounding
  Box Regression
Alpha-IoU: A Family of Power Intersection over Union Losses for Bounding Box Regression
Jiabo He
S. Erfani
Xingjun Ma
James Bailey
Ying Chi
Xiansheng Hua
59
256
0
26 Oct 2021
Noisy Annotation Refinement for Object Detection
Noisy Annotation Refinement for Object Detection
Jiafeng Mao
Qing Yu
Yoko Yamakata
Kiyoharu Aizawa
NoLa
73
11
0
20 Oct 2021
End-to-End Semi-Supervised Object Detection with Soft Teacher
End-to-End Semi-Supervised Object Detection with Soft Teacher
Mengde Xu
Zheng Zhang
Han Hu
Jianfeng Wang
Lijuan Wang
Fangyun Wei
X. Bai
Zicheng Liu
63
495
0
16 Jun 2021
Boosting Co-teaching with Compression Regularization for Label Noise
Boosting Co-teaching with Compression Regularization for Label Noise
Yingyi Chen
Xin Shen
S. Hu
Johan A. K. Suykens
NoLa
71
46
0
28 Apr 2021
Unbiased Teacher for Semi-Supervised Object Detection
Unbiased Teacher for Semi-Supervised Object Detection
Yen-Cheng Liu
Chih-Yao Ma
Zijian He
Chia-Wen Kuo
Kan Chen
Peizhao Zhang
Bichen Wu
Z. Kira
Peter Vajda
103
484
0
18 Feb 2021
Co-mining: Self-Supervised Learning for Sparsely Annotated Object
  Detection
Co-mining: Self-Supervised Learning for Sparsely Annotated Object Detection
Tiancai Wang
Tong Yang
Jiale Cao
Xinming Zhang
40
47
0
03 Dec 2020
TIDE: A General Toolbox for Identifying Object Detection Errors
TIDE: A General Toolbox for Identifying Object Detection Errors
Daniel Bolya
Sean Foley
James Hays
Judy Hoffman
76
195
0
18 Aug 2020
Map-Repair: Deep Cadastre Maps Alignment and Temporal Inconsistencies
  Fix in Satellite Images
Map-Repair: Deep Cadastre Maps Alignment and Temporal Inconsistencies Fix in Satellite Images
Stefano Zorzi
K. Bittner
Friedrich Fraundorfer
28
4
0
24 Jul 2020
Learning to segment from misaligned and partial labels
Learning to segment from misaligned and partial labels
Simone Fobi
Terence Conlon
Jay Taneja
V. Modi
90
7
0
27 May 2020
A Simple Semi-Supervised Learning Framework for Object Detection
A Simple Semi-Supervised Learning Framework for Object Detection
Kihyuk Sohn
Zizhao Zhang
Chun-Liang Li
Han Zhang
Chen-Yu Lee
Tomas Pfister
78
497
0
10 May 2020
Instance-aware, Context-focused, and Memory-efficient Weakly Supervised
  Object Detection
Instance-aware, Context-focused, and Memory-efficient Weakly Supervised Object Detection
Zhongzheng Ren
Zhiding Yu
Xiaodong Yang
Xuan Li
Yong Jae Lee
Alex Schwing
Jan Kautz
WSOD
62
201
0
09 Apr 2020
Towards Noise-resistant Object Detection with Noisy Annotations
Towards Noise-resistant Object Detection with Noisy Annotations
Junnan Li
Caiming Xiong
R. Socher
Guosheng Lin
ObjD
NoLa
126
31
0
03 Mar 2020
DivideMix: Learning with Noisy Labels as Semi-supervised Learning
DivideMix: Learning with Noisy Labels as Semi-supervised Learning
Junnan Li
R. Socher
Guosheng Lin
NoLa
105
1,029
0
18 Feb 2020
Solving Missing-Annotation Object Detection with Background
  Recalibration Loss
Solving Missing-Annotation Object Detection with Background Recalibration Loss
Han Zhang
Fangyi Chen
Zhiqiang Shen
Qiqi Hao
Chenchen Zhu
Marios Savvides
ObjD
159
52
0
12 Feb 2020
Unsupervised Domain Adaptation for Object Detection via Cross-Domain
  Semi-Supervised Learning
Unsupervised Domain Adaptation for Object Detection via Cross-Domain Semi-Supervised Learning
Fuxun Yu
Di Wang
Yinpeng Chen
Nikolaos Karianakis
Tong Shen
Pei Yu
Dimitrios Lymberopoulos
Sidi Lu
Weisong Shi
Xiang Chen
55
33
0
17 Nov 2019
Object Detection in Optical Remote Sensing Images: A Survey and A New
  Benchmark
Object Detection in Optical Remote Sensing Images: A Survey and A New Benchmark
Ke Li
G. Wan
Gong Cheng
L. Meng
Junwei Han
55
1,449
0
31 Aug 2019
FCOS: Fully Convolutional One-Stage Object Detection
FCOS: Fully Convolutional One-Stage Object Detection
Zhi Tian
Chunhua Shen
Hao Chen
Tong He
ObjD
123
5,007
0
02 Apr 2019
Generalized Intersection over Union: A Metric and A Loss for Bounding
  Box Regression
Generalized Intersection over Union: A Metric and A Loss for Bounding Box Regression
S. Hamid Rezatofighi
Deyuan Li
JunYoung Gwak
Amir Sadeghian
Ian Reid
Silvio Savarese
147
4,163
0
25 Feb 2019
NOTE-RCNN: NOise Tolerant Ensemble RCNN for Semi-Supervised Object
  Detection
NOTE-RCNN: NOise Tolerant Ensemble RCNN for Semi-Supervised Object Detection
J. Gao
Jiang Wang
Shengyang Dai
Li Li
Ram Nevatia
ObjD
67
94
0
01 Dec 2018
TS2C: Tight Box Mining with Surrounding Segmentation Context for Weakly
  Supervised Object Detection
TS2C: Tight Box Mining with Surrounding Segmentation Context for Weakly Supervised Object Detection
Yunchao Wei
Zhiqiang Shen
Bowen Cheng
Humphrey Shi
Jinjun Xiong
Jiashi Feng
Thomas Huang
WSOD
48
153
0
13 Jul 2018
PCL: Proposal Cluster Learning for Weakly Supervised Object Detection
PCL: Proposal Cluster Learning for Weakly Supervised Object Detection
Peng Tang
Xinggang Wang
S. Bai
Wei Shen
X. Bai
Wenyu Liu
Alan Yuille
WSOD
70
367
0
09 Jul 2018
Soft Sampling for Robust Object Detection
Soft Sampling for Robust Object Detection
Zhe Wu
Navaneeth Bodla
Bharat Singh
Mahyar Najibi
Rama Chellappa
L. Davis
ObjD
51
72
0
18 Jun 2018
Co-teaching: Robust Training of Deep Neural Networks with Extremely
  Noisy Labels
Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels
Bo Han
Quanming Yao
Xingrui Yu
Gang Niu
Miao Xu
Weihua Hu
Ivor Tsang
Masashi Sugiyama
NoLa
110
2,067
0
18 Apr 2018
Robust Loss Functions under Label Noise for Deep Neural Networks
Robust Loss Functions under Label Noise for Deep Neural Networks
Aritra Ghosh
Himanshu Kumar
P. Sastry
NoLa
OOD
67
956
0
27 Dec 2017
MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks
  on Corrupted Labels
MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks on Corrupted Labels
Lu Jiang
Zhengyuan Zhou
Thomas Leung
Li Li
Li Fei-Fei
NoLa
95
1,452
0
14 Dec 2017
Focal Loss for Dense Object Detection
Focal Loss for Dense Object Detection
Nayeon Lee
Priya Goyal
Ross B. Girshick
Kaiming He
Piotr Dollár
ObjD
112
2,996
0
07 Aug 2017
A Large Contextual Dataset for Classification, Detection and Counting of
  Cars with Deep Learning
A Large Contextual Dataset for Classification, Detection and Counting of Cars with Deep Learning
T. Nathan Mundhenk
G. Konjevod
W. Sakla
K. Boakye
76
337
0
14 Sep 2016
A Survey on Object Detection in Optical Remote Sensing Images
A Survey on Object Detection in Optical Remote Sensing Images
Gong Cheng
Junwei Han
ObjD
58
1,177
0
20 Mar 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
2.2K
193,878
0
10 Dec 2015
Weakly Supervised Deep Detection Networks
Weakly Supervised Deep Detection Networks
Hakan Bilen
Andrea Vedaldi
WSOD
69
789
0
09 Nov 2015
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal
  Networks
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
Shaoqing Ren
Kaiming He
Ross B. Girshick
Jian Sun
AIMat
ObjD
499
62,270
0
04 Jun 2015
Microsoft COCO: Common Objects in Context
Microsoft COCO: Common Objects in Context
Nayeon Lee
Michael Maire
Serge J. Belongie
Lubomir Bourdev
Ross B. Girshick
James Hays
Pietro Perona
Deva Ramanan
C. L. Zitnick
Piotr Dollár
ObjD
413
43,638
0
01 May 2014
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