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v1v2 (latest)

CPRAL: Collaborative Panoptic-Regional Active Learning for Semantic Segmentation

11 December 2021
Yu Qiao
Jincheng Zhu
Chengjiang Long
Zeyao Zhang
Yuxin Wang
Z. Du
Xin Yang
ArXiv (abs)PDFHTML

Papers citing "CPRAL: Collaborative Panoptic-Regional Active Learning for Semantic Segmentation"

37 / 37 papers shown
Title
Multiple instance active learning for object detection
Multiple instance active learning for object detection
Tianning Yuan
Fang Wan
Mengying Fu
Jianzhuang Liu
Songcen Xu
Xiangyang Ji
QiXiang Ye
WSOD
89
123
0
06 Apr 2021
Smart Scribbles for Image Mating
Smart Scribbles for Image Mating
Xin Yang
Yu Qiao
Shaozhe Chen
Shengfeng He
Baocai Yin
Qiang Zhang
Xiaopeng Wei
Rynson W. H. Lau
85
18
0
31 Mar 2021
Multi-scale Information Assembly for Image Matting
Multi-scale Information Assembly for Image Matting
Yu Qiao
Yuhao Liu
Qiang Zhu
Xin Yang
Yuxin Wang
Qiang Zhang
Xiaopeng Wei
54
14
0
07 Jan 2021
MetaBox+: A new Region Based Active Learning Method for Semantic
  Segmentation using Priority Maps
MetaBox+: A new Region Based Active Learning Method for Semantic Segmentation using Priority Maps
Pascal Colling
L. Roese-Koerner
Hanno Gottschalk
Matthias Rottmann
51
26
0
05 Oct 2020
Suggestive Annotation of Brain Tumour Images with Gradient-guided
  Sampling
Suggestive Annotation of Brain Tumour Images with Gradient-guided Sampling
Chengliang Dai
Shuo Wang
Yuanhan Mo
Kaichen Zhou
Elsa D. Angelini
Yike Guo
Wenjia Bai
MedIm
53
33
0
26 Jun 2020
Sequential Graph Convolutional Network for Active Learning
Sequential Graph Convolutional Network for Active Learning
Razvan Caramalau
Binod Bhattarai
Tae-Kyun Kim
GNN
104
122
0
18 Jun 2020
State-Relabeling Adversarial Active Learning
State-Relabeling Adversarial Active Learning
Beichen Zhang
Liang Li
Shijie Yang
Shuhui Wang
Zhengjun Zha
Qingming Huang
63
128
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 Learning
Jongwon Choi
K. M. Yi
Jihoon Kim
Jincho Choo
Byoungjip Kim
Jin-Yeop Chang
Youngjune Gwon
H. Chang
DRL
55
42
0
25 Mar 2020
Deep Active Learning for Biased Datasets via Fisher Kernel
  Self-Supervision
Deep Active Learning for Biased Datasets via Fisher Kernel Self-Supervision
Denis A. Gudovskiy
Alec Hodgkinson
Takuya Yamaguchi
Sotaro Tsukizawa
FedML
46
59
0
01 Mar 2020
Reinforced active learning for image segmentation
Reinforced active learning for image segmentation
Arantxa Casanova
Pedro H. O. Pinheiro
Negar Rostamzadeh
C. Pal
47
108
0
16 Feb 2020
Task-Aware Variational Adversarial Active Learning
Task-Aware Variational Adversarial Active Learning
Kwanyoung Kim
Dongwon Park
K. Kim
S. Chun
VLMOOD
46
144
0
11 Feb 2020
ViewAL: Active Learning with Viewpoint Entropy for Semantic Segmentation
ViewAL: Active Learning with Viewpoint Entropy for Semantic Segmentation
Yawar Siddiqui
Julien P. C. Valentin
Matthias Nießner
59
159
0
26 Nov 2019
Active Learning for Deep Detection Neural Networks
Active Learning for Deep Detection Neural Networks
H. H. Aghdam
Abel Gonzalez-Garcia
Joost van de Weijer
Antonio M. López
VLMObjD
87
139
0
20 Nov 2019
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
82
65
0
16 Oct 2019
BatchBALD: Efficient and Diverse Batch Acquisition for Deep Bayesian
  Active Learning
BatchBALD: Efficient and Diverse Batch Acquisition for Deep Bayesian Active Learning
Andreas Kirsch
Joost R. van Amersfoort
Y. Gal
FedML
87
629
0
19 Jun 2019
Uncertainty-guided Continual Learning with Bayesian Neural Networks
Uncertainty-guided Continual Learning with Bayesian Neural Networks
Sayna Ebrahimi
Mohamed Elhoseiny
Trevor Darrell
Marcus Rohrbach
CLLBDL
61
197
0
06 Jun 2019
Learning Loss for Active Learning
Learning Loss for Active Learning
Donggeun Yoo
In So Kweon
UQCV
85
662
0
09 May 2019
Variational Adversarial Active Learning
Variational Adversarial Active Learning
Samarth Sinha
Sayna Ebrahimi
Trevor Darrell
GANDRLVLMSSL
122
579
0
31 Mar 2019
FickleNet: Weakly and Semi-supervised Semantic Image Segmentation using
  Stochastic Inference
FickleNet: Weakly and Semi-supervised Semantic Image Segmentation using Stochastic Inference
Jungbeom Lee
Eunji Kim
Sungmin Lee
Jangho Lee
Sungroh Yoon
68
422
0
27 Feb 2019
CEREALS - Cost-Effective REgion-based Active Learning for Semantic
  Segmentation
CEREALS - Cost-Effective REgion-based Active Learning for Semantic Segmentation
Radek Mackowiak
Philip Lenz
Omair Ghori
Ferran Diego
O. Lange
Carsten Rother
79
108
0
23 Oct 2018
Cost-Sensitive Active Learning for Intracranial Hemorrhage Detection
Cost-Sensitive Active Learning for Intracranial Hemorrhage Detection
Weicheng Kuo
Christian Häne
E. Yuh
P. Mukherjee
Jitendra Malik
OOD
57
98
0
08 Sep 2018
Adversarial Sampling for Active Learning
Adversarial Sampling for Active Learning
Christoph Mayer
Radu Timofte
GAN
123
117
0
20 Aug 2018
Active Learning for Segmentation by Optimizing Content Information for
  Maximal Entropy
Active Learning for Segmentation by Optimizing Content Information for Maximal Entropy
Firat Özdemir
Z. Peng
C. Tanner
Philipp Fürnstahl
O. Goksel
58
28
0
18 Jul 2018
Efficient Active Learning for Image Classification and Segmentation
  using a Sample Selection and Conditional Generative Adversarial Network
Efficient Active Learning for Image Classification and Segmentation using a Sample Selection and Conditional Generative Adversarial Network
Dwarikanath Mahapatra
Behzad Bozorgtabar
Jean-Philippe Thiran
M. Reyes
GANMedIm
97
176
0
14 Jun 2018
BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning
BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning
Feng Yu
Haofeng Chen
Xin Wang
Wenqi Xian
Yingying Chen
Fangchen Liu
Vashisht Madhavan
Trevor Darrell
VLM
344
2,150
0
12 May 2018
Learning Pixel-level Semantic Affinity with Image-level Supervision for
  Weakly Supervised Semantic Segmentation
Learning Pixel-level Semantic Affinity with Image-level Supervision for Weakly Supervised Semantic Segmentation
Jiwoon Ahn
Suha Kwak
285
746
0
28 Mar 2018
Generative Image Inpainting with Contextual Attention
Generative Image Inpainting with Contextual Attention
Jiahui Yu
Zhe Lin
Jimei Yang
Xiaohui Shen
Xin Lu
Thomas S. Huang
GANDiffM
103
2,266
0
24 Jan 2018
MobileNetV2: Inverted Residuals and Linear Bottlenecks
MobileNetV2: Inverted Residuals and Linear Bottlenecks
Mark Sandler
Andrew G. Howard
Menglong Zhu
A. Zhmoginov
Liang-Chieh Chen
192
19,316
0
13 Jan 2018
Cost-Effective Active Learning for Melanoma Segmentation
Cost-Effective Active Learning for Melanoma Segmentation
Marc Górriz
Axel Carlier
Emmanuel Faure
Xavier Giró-i-Nieto
55
119
0
24 Nov 2017
Rethinking Atrous Convolution for Semantic Image Segmentation
Rethinking Atrous Convolution for Semantic Image Segmentation
Liang-Chieh Chen
George Papandreou
Florian Schroff
Hartwig Adam
SSeg
232
8,481
0
17 Jun 2017
Suggestive Annotation: A Deep Active Learning Framework for Biomedical
  Image Segmentation
Suggestive Annotation: A Deep Active Learning Framework for Biomedical Image Segmentation
Ling Yang
Yizhe Zhang
Jianxu Chen
Siyuan Zhang
Danny Chen
MedIm
73
505
0
15 Jun 2017
Dilated Residual Networks
Dilated Residual Networks
Feng Yu
V. Koltun
Thomas Funkhouser
MedIm
129
1,620
0
28 May 2017
Deep Bayesian Active Learning with Image Data
Deep Bayesian Active Learning with Image Data
Y. Gal
Riashat Islam
Zoubin Ghahramani
BDLUQCV
73
1,739
0
08 Mar 2017
Feature Pyramid Networks for Object Detection
Feature Pyramid Networks for Object Detection
Nayeon Lee
Piotr Dollár
Ross B. Girshick
Kaiming He
Bharath Hariharan
Serge J. Belongie
ObjD
483
22,134
0
09 Dec 2016
Semi-Supervised Classification with Graph Convolutional Networks
Semi-Supervised Classification with Graph Convolutional Networks
Thomas Kipf
Max Welling
GNNSSL
652
29,154
0
09 Sep 2016
The Cityscapes Dataset for Semantic Urban Scene Understanding
The Cityscapes Dataset for Semantic Urban Scene Understanding
Marius Cordts
Mohamed Omran
Sebastian Ramos
Timo Rehfeld
Markus Enzweiler
Rodrigo Benenson
Uwe Franke
Stefan Roth
Bernt Schiele
1.1K
11,641
0
06 Apr 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCVBDL
836
9,345
0
06 Jun 2015
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