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Hierarchical Subquery Evaluation for Active Learning on a Graph

Hierarchical Subquery Evaluation for Active Learning on a Graph

30 April 2015
Oisin Mac Aodha
Neill D. F. Campbell
Jan Kautz
Gabriel J. Brostow
ArXiv (abs)PDFHTML

Papers citing "Hierarchical Subquery Evaluation for Active Learning on a Graph"

34 / 34 papers shown
Table Detection with Active Learning
Table Detection with Active LearningIEEE International Conference on Document Analysis and Recognition (ICDAR), 2025
Somraj Gautam
Nachiketa Purohit
Gaurav Harit
157
0
0
24 Sep 2025
KECOR: Kernel Coding Rate Maximization for Active 3D Object Detection
KECOR: Kernel Coding Rate Maximization for Active 3D Object DetectionIEEE International Conference on Computer Vision (ICCV), 2023
Yadan Luo
Zhuoxiao Chen
Zhenying Fang
Zheng Zhang
Zi Huang
Mahsa Baktashmotlagh
3DPC
233
17
0
16 Jul 2023
Exploring Active 3D Object Detection from a Generalization Perspective
Exploring Active 3D Object Detection from a Generalization PerspectiveInternational Conference on Learning Representations (ICLR), 2023
Yadan Luo
Zhuoxiao Chen
Zijian Wang
Xin Yu
Zi Huang
Mahsa Baktash
3DPC
231
34
0
23 Jan 2023
Active Learning Guided by Efficient Surrogate Learners
Active Learning Guided by Efficient Surrogate LearnersAAAI Conference on Artificial Intelligence (AAAI), 2023
Yunpyo An
Suyeong Park
K. Kim
166
1
0
07 Jan 2023
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
198
27
0
27 Nov 2022
Plug and Play Active Learning for Object Detection
Plug and Play Active Learning for Object DetectionComputer Vision and Pattern Recognition (CVPR), 2022
Chenhongyi Yang
Lichao Huang
Elliot J. Crowley
ObjD
240
31
0
21 Nov 2022
Deep Active Learning with Noise Stability
Deep Active Learning with Noise StabilityAAAI Conference on Artificial Intelligence (AAAI), 2022
Xingjian Li
Pengkun Yang
Mingkun Xu
Xueying Zhan
Tianyang Wang
Dejing Dou
Chengzhong Xu
UQCV
165
24
0
26 May 2022
Anomaly Clustering: Grouping Images into Coherent Clusters of Anomaly
  Types
Anomaly Clustering: Grouping Images into Coherent Clusters of Anomaly TypesIEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2021
Kihyuk Sohn
Chang Jo Kim
Chun-Liang Li
Chen-Yu Lee
Tomas Pfister
194
23
0
21 Dec 2021
Boosting Active Learning via Improving Test Performance
Boosting Active Learning via Improving Test Performance
Tianyang Wang
Xingjian Li
Pengkun Yang
Guosheng Hu
Xiangrui Zeng
Siyu Huang
Chengzhong Xu
Min Xu
182
39
0
10 Dec 2021
Scaling up instance annotation via label propagation
Scaling up instance annotation via label propagation
Dim P. Papadopoulos
Ethan Weber
Antonio Torralba
ISeg
224
13
0
05 Oct 2021
Influence Selection for Active Learning
Influence Selection for Active Learning
Zhuoming Liu
Hao Ding
Huaping Zhong
Weijia Li
Jifeng Dai
Conghui He
TDI
287
119
0
20 Aug 2021
Multiple instance active learning for object detection
Multiple instance active learning for object detectionComputer Vision and Pattern Recognition (CVPR), 2021
Tianning Yuan
Fang Wan
Mengying Fu
Jianzhuang Liu
Songcen Xu
Xiangyang Ji
QiXiang Ye
WSOD
280
149
0
06 Apr 2021
Active Learning to Classify Macromolecular Structures in situ for Less
  Supervision in Cryo-Electron Tomography
Active Learning to Classify Macromolecular Structures in situ for Less Supervision in Cryo-Electron Tomography
Xuefeng Du
Haohan Wang
Zhenxi Zhu
Xiangrui Zeng
Yi-Wei Chang
Jing Zhang
Min Xu
141
11
0
24 Feb 2021
LSCALE: Latent Space Clustering-Based Active Learning for Node
  Classification
LSCALE: Latent Space Clustering-Based Active Learning for Node Classification
Juncheng Liu
Yiwei Wang
Bryan Hooi
Renchi Yang
X. Xiao
237
7
0
13 Dec 2020
Exploiting Context for Robustness to Label Noise in Active Learning
Exploiting Context for Robustness to Label Noise in Active Learning
Sudipta Paul
S. Chandrasekaran
B. S. Manjunath
Amit K. Roy-Chowdhury
NoLa
120
5
0
18 Oct 2020
A Survey on Large-scale Machine Learning
A Survey on Large-scale Machine LearningIEEE Transactions on Knowledge and Data Engineering (TKDE), 2020
Meng Wang
Weijie Fu
Xiangnan He
Shijie Hao
Xindong Wu
187
141
0
10 Aug 2020
MetAL: Active Semi-Supervised Learning on Graphs via Meta Learning
MetAL: Active Semi-Supervised Learning on Graphs via Meta Learning
Kaushalya Madhawa
T. Murata
AI4CE
169
9
0
22 Jul 2020
State-Relabeling Adversarial Active Learning
State-Relabeling Adversarial Active LearningComputer Vision and Pattern Recognition (CVPR), 2020
Beichen Zhang
Liang Li
Shijie Yang
Shuhui Wang
Zhengjun Zha
Qingming Huang
141
140
0
10 Apr 2020
VaB-AL: Incorporating Class Imbalance and Difficulty with Variational
  Bayes for Active Learning
VaB-AL: Incorporating Class Imbalance and Difficulty with Variational Bayes for Active LearningComputer Vision and Pattern Recognition (CVPR), 2020
Jongwon Choi
K. M. Yi
Jihoon Kim
Jincho Choo
Byoungjip Kim
Jin-Yeop Chang
Youngjune Gwon
H. Chang
DRL
225
50
0
25 Mar 2020
Task-Aware Variational Adversarial Active Learning
Task-Aware Variational Adversarial Active LearningComputer Vision and Pattern Recognition (CVPR), 2020
Kwanyoung Kim
Dongwon Park
K. Kim
S. Chun
VLMOOD
163
172
0
11 Feb 2020
Active Learning for Graph Neural Networks via Node Feature Propagation
Active Learning for Graph Neural Networks via Node Feature Propagation
Yuexin Wu
Yichong Xu
Aarti Singh
Yiming Yang
A. Dubrawski
GNNAI4CE
180
71
0
16 Oct 2019
Consistency-based Semi-supervised Active Learning: Towards Minimizing
  Labeling Cost
Consistency-based Semi-supervised Active Learning: Towards Minimizing Labeling CostEuropean Conference on Computer Vision (ECCV), 2019
M. Gao
Zizhao Zhang
Guo-Ding Yu
Sercan O. Arik
L. Davis
Tomas Pfister
379
228
0
16 Oct 2019
Learning Loss for Active Learning
Learning Loss for Active LearningComputer Vision and Pattern Recognition (CVPR), 2019
Donggeun Yoo
In So Kweon
UQCV
297
749
0
09 May 2019
Exploring Representativeness and Informativeness for Active Learning
Exploring Representativeness and Informativeness for Active Learning
Bo Du
Zengmao Wang
Lefei Zhang
Liangpei Zhang
Wen Liu
Jialie Shen
Dacheng Tao
114
183
0
14 Apr 2019
Context-Aware Query Selection for Active Learning in Event Recognition
Context-Aware Query Selection for Active Learning in Event Recognition
Mahmudul Hasan
S. Paul
Anastasios I. Mourikis
Amit K. Roy-Chowdhury
99
17
0
09 Apr 2019
Give me a hint! Navigating Image Databases using Human-in-the-loop
  Feedback
Give me a hint! Navigating Image Databases using Human-in-the-loop Feedback
Bryan A. Plummer
M. Kiapour
Shuai Zheng
Robinson Piramuthu
167
19
0
24 Sep 2018
Bayesian Semi-supervised Learning with Graph Gaussian Processes
Bayesian Semi-supervised Learning with Graph Gaussian Processes
Yin Cheng Ng
Nicolo Colombo
Ricardo M. A. Silva
BDL
329
93
0
12 Sep 2018
Multi-class Active Learning: A Hybrid Informative and Representative
  Criterion Inspired Approach
Multi-class Active Learning: A Hybrid Informative and Representative Criterion Inspired Approach
Xi Fang
Zengmao Wang
Xinyao Tang
Lefei Zhang
48
2
0
06 Mar 2018
Active Expansion Sampling for Learning Feasible Domains in an Unbounded
  Input Space
Active Expansion Sampling for Learning Feasible Domains in an Unbounded Input Space
Wei Chen
M. Fuge
113
18
0
25 Aug 2017
Temporal Model Adaptation for Person Re-Identification
Temporal Model Adaptation for Person Re-Identification
N. Martinel
Abir Das
C. Micheloni
Amit K. Roy-Chowdhury
OOD
168
123
0
25 Jul 2016
Continuous Adaptation of Multi-Camera Person Identification Models
  through Sparse Non-redundant Representative Selection
Continuous Adaptation of Multi-Camera Person Identification Models through Sparse Non-redundant Representative SelectionComputer Vision and Image Understanding (CVIU), 2016
Abir Das
Yikang Shen
Amit K. Roy-Chowdhury
3DH
106
9
0
01 Jul 2016
Active Learning for Delineation of Curvilinear Structures
Active Learning for Delineation of Curvilinear Structures
Agata Mosinska-Domanska
Raphael Sznitman
Przemyslaw Glowacki
Pascal Fua
129
17
0
02 Dec 2015
The Unreasonable Effectiveness of Noisy Data for Fine-Grained
  Recognition
The Unreasonable Effectiveness of Noisy Data for Fine-Grained Recognition
J. Krause
Benjamin Sapp
Andrew Howard
Howard Zhou
Alexander Toshev
Tom Duerig
James Philbin
Fei-Fei Li
305
369
0
20 Nov 2015
Becoming the Expert - Interactive Multi-Class Machine Teaching
Becoming the Expert - Interactive Multi-Class Machine Teaching
Edward Johns
Oisin Mac Aodha
Gabriel J. Brostow
165
75
0
28 Apr 2015
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