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An Adaptive Supervision Framework for Active Learning in Object
  Detection
v1v2v3 (latest)

An Adaptive Supervision Framework for Active Learning in Object Detection

British Machine Vision Conference (BMVC), 2019
7 August 2019
Sai Vikas Desai
Akshay L Chandra
Wei Guo
S. Ninomiya
V. Balasubramanian
ArXiv (abs)PDFHTML

Papers citing "An Adaptive Supervision Framework for Active Learning in Object Detection"

21 / 21 papers shown
ALWOD: Active Learning for Weakly-Supervised Object Detection
ALWOD: Active Learning for Weakly-Supervised Object DetectionIEEE International Conference on Computer Vision (ICCV), 2023
Yuting Wang
Velibor Ilic
Jiatong Li
B. Kisačanin
Vladimir Pavlovic
267
15
0
14 Sep 2023
Multi-Task Consistency for Active Learning
Multi-Task Consistency for Active Learning
A. Hekimoglu
Philipp Friedrich
Walter Zimmer
Michael Schmidt
Alvaro Marcos-Ramiro
Alois C. Knoll
VLM
266
12
0
21 Jun 2023
Box-Level Active Detection
Box-Level Active DetectionComputer Vision and Pattern Recognition (CVPR), 2023
Mengyao Lyu
Jundong Zhou
Hui Chen
Yijie Huang
Dongdong Yu
Yaqian Li
Yandong Guo
Yuchen Guo
Liuyu Xiang
Guiguang Ding
VLMObjD
195
23
0
23 Mar 2023
Identifying Label Errors in Object Detection Datasets by Loss Inspection
Identifying Label Errors in Object Detection Datasets by Loss InspectionIEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2023
Marius Schubert
Tobias Riedlinger
Karsten Kahl
Daniel Kröll
S. Schoenen
Sinisa Segvic
Matthias Rottmann
NoLa
343
19
0
13 Mar 2023
Towards Rapid Prototyping and Comparability in Active Learning for Deep
  Object Detection
Towards Rapid Prototyping and Comparability in Active Learning for Deep Object Detection
Tobias Riedlinger
Marius Schubert
Karsten Kahl
Hanno Gottschalk
Matthias Rottmann
VLMObjD
229
3
0
21 Dec 2022
Deep Active Learning for Computer Vision: Past and Future
Deep Active Learning for Computer Vision: Past and FutureAPSIPA Transactions on Signal and Information Processing (TASIP), 2022
Rinyoichi Takezoe
Xu Liu
Shunan Mao
Marco Tianyu Chen
Zhanpeng Feng
Shiliang Zhang
Xiaoyu Wang
VLM
203
28
0
27 Nov 2022
Active Learning Strategies for Weakly-supervised Object Detection
Active Learning Strategies for Weakly-supervised Object DetectionEuropean Conference on Computer Vision (ECCV), 2022
Huy V. Vo
Oriane Siméoni
Spyros Gidaris
Andrei Bursuc
Patrick Pérez
Jean Ponce
348
26
0
25 Jul 2022
Active Pointly-Supervised Instance Segmentation
Active Pointly-Supervised Instance SegmentationEuropean Conference on Computer Vision (ECCV), 2022
Chufeng Tang
Lingxi Xie
Qiang Chen
Xiaopeng Zhang
Qi Tian
Xiaolin Hu
ISeg
387
20
0
23 Jul 2022
TALISMAN: Targeted Active Learning for Object Detection with Rare
  Classes and Slices using Submodular Mutual Information
TALISMAN: Targeted Active Learning for Object Detection with Rare Classes and Slices using Submodular Mutual Information
Suraj Kothawade
Saikat Ghosh
Sumit Shekhar
Yu Xiang
Rishabh K. Iyer
270
36
0
30 Nov 2021
OPAD: An Optimized Policy-based Active Learning Framework for Document
  Content Analysis
OPAD: An Optimized Policy-based Active Learning Framework for Document Content Analysis
Sumit Shekhar
Bhanu Prakash Reddy Guda
Ashutosh Chaubey
Ishan Jindal
Avanish Jain
225
0
0
01 Oct 2021
Region-level Active Detector Learning
Region-level Active Detector Learning
Michael Laielli
Giscard Biamby
Dian Chen
Ritwik Gupta
Adam Loeffler
P. Nguyen
R. Luo
Trevor Darrell
Sayna Ebrahimi
ObjD
172
3
0
20 Aug 2021
Weakly-Supervised Object Detection Learning through Human-Robot
  Interaction
Weakly-Supervised Object Detection Learning through Human-Robot InteractionIEEE-RAS International Conference on Humanoid Robots (Humanoids), 2021
Elisa Maiettini
V. Tikhanoff
Lorenzo Natale
157
7
0
16 Jul 2021
Not All Labels Are Equal: Rationalizing The Labeling Costs for Training
  Object Detection
Not All Labels Are Equal: Rationalizing The Labeling Costs for Training Object DetectionComputer Vision and Pattern Recognition (CVPR), 2021
Ismail Elezi
Zhiding Yu
Anima Anandkumar
Laura Leal-Taixe
J. Álvarez
ObjD
241
53
0
22 Jun 2021
Sample selection for efficient image annotation
Sample selection for efficient image annotationEuropean Workshop on Visual Information Processing (EUVIP), 2021
Bishwo Adhikari
Esa Rahtu
H. Huttunen
148
8
0
10 May 2021
Inspect, Understand, Overcome: A Survey of Practical Methods for AI
  Safety
Inspect, Understand, Overcome: A Survey of Practical Methods for AI Safety
Sebastian Houben
Stephanie Abrecht
Maram Akila
Andreas Bär
Felix Brockherde
...
Serin Varghese
Michael Weber
Sebastian J. Wirkert
Tim Wirtz
Matthias Woehrle
AAML
352
61
0
29 Apr 2021
Consistency-based Active Learning for Object Detection
Consistency-based Active Learning for Object Detection
Weiping Yu
Sijie Zhu
Taojiannan Yang
Chong Chen
ObjD
337
65
0
18 Mar 2021
From Handheld to Unconstrained Object Detection: a Weakly-supervised
  On-line Learning Approach
From Handheld to Unconstrained Object Detection: a Weakly-supervised On-line Learning ApproachIEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), 2020
Elisa Maiettini
Andrea Maracani
Raffaello Camoriano
Giulia Pasquale
V. Tikhanoff
Lorenzo Rosasco
Lorenzo Natale
228
0
0
28 Dec 2020
Semi-supervised Active Learning for Instance Segmentation via Scoring
  Predictions
Semi-supervised Active Learning for Instance Segmentation via Scoring Predictions
Jun Wang
Shaoguo Wen
Kaixing Chen
Jianghua Yu
Xiaoxia Zhou
Peng Gao
Changsheng Li
Guotong Xie
ISeg
152
19
0
09 Dec 2020
A Weakly Supervised Region-Based Active Learning Method for COVID-19
  Segmentation in CT Images
A Weakly Supervised Region-Based Active Learning Method for COVID-19 Segmentation in CT Images
I. Laradji
Pau Rodríguez López
Frederic Branchaud-Charron
Keegan Lensink
Parmida Atighehchian
William Parker
David Vazquez
Derek Nowrouzezahrai
215
21
0
07 Jul 2020
Computer Vision with Deep Learning for Plant Phenotyping in Agriculture:
  A Survey
Computer Vision with Deep Learning for Plant Phenotyping in Agriculture: A Survey
Akshay L Chandra
Sai Vikas Desai
W. Guo
V. Balasubramanian
180
55
0
18 Jun 2020
Scalable Active Learning for Object Detection
Scalable Active Learning for Object Detection
Elmar Haussmann
Michele Fenzi
Kashyap Chitta
J. Ivanecký
Hanson Xu
D. Roy
Akshita Mittel
Nicolas Koumchatzky
C. Farabet
J. Álvarez
173
123
0
09 Apr 2020
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