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Recent works on click-based interactive segmentation have demonstrated state-of-the-art results by using various inference-time optimization schemes.
The open images dataset v4,
A. Kuznetsova, H. Rom, N. Alldrin, J. Uijlings, I. Krasin, J. Pont-Tuset, S. Kamali, S. Popov, M. Malloci, A. Kolesnikov, T. Duerig, V. Ferrari, · 1981
Earlier work this paper cites.
Interactive graph cuts for optimal boundary & region segmentation of objects in n-d images,
Y. Boykov, M.-P. Jolly, · 2001
Earlier work this paper cites.
A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics,
D. Martin, C. Fowlkes, D. Tal, J. Malik, · 2001
Earlier work this paper cites.
“GrabCut”
C. Rother, V. Kolmogorov, A. Blake, · 2004
Earlier work this paper cites.
Interactive graph cut based segmentation with shape priors,
D. Freedman, T. Zhang, · 2005
Earlier work this paper cites.
Random walks for image segmentation,
L. Grady, · 2006
Earlier work this paper cites.
Generative image segmentation using random walks with restart,
T. H. Kim, K. M. Lee, S. U. Lee, · 2008
Earlier work this paper cites.
ImageNet: A large-scale hierarchical image database,
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, L. Fei-Fei, · 2009
Earlier work this paper cites.
The pascal visual object classes (VOC) challenge,
M. Everingham, L. V. Gool, C. K. I. Williams, J. Winn, A. Zisserman, · 2009
Earlier work this paper cites.
Geodesic star convexity for interactive image segmentation,
V. Gulshan, C. Rother, A. Criminisi, A. Blake, A. Zisserman, · 2010
Earlier work this paper cites.
A comparative evaluation of interactive segmentation algorithms,
K. McGuinness, N. E. O’Connor, · 2010
Earlier work this paper cites.
Semantic contours from inverse detectors,
B. Hariharan, P. Arbelaez, L. Bourdev, S. Maji, J. Malik, · 2011
Earlier work this paper cites.
Error-tolerant scribbles based interactive image segmentation,
J. Bai, X. Wu, · 2014
Earlier work this paper cites.
Microsoft COCO: Common objects in context,
T.-Y. Lin, M. Maire, S. Belongie, J. Hays, P. Perona, D. Ramanan, P. Dollár, C. L. Zitnick, · 2014
Earlier work this paper cites.
MILCut: A sweeping line multiple instance learning paradigm for interactive image segmentation,
J. Wu, Y. Zhao, J.-Y. Zhu, S. Luo, Z. Tu, · 2014
Earlier work this paper cites.
DenseCut: Densely connected CRFs for realtime GrabCut,
M. M. Cheng, V. A. Prisacariu, S. Zheng, P. H. S. Torr, C. Rother, · 2015
Earlier work this paper cites.
Deep interactive object selection,
N. Xu, B. Price, S. Cohen, J. Yang, T. Huang, · 2016
Earlier work this paper cites.
ScribbleSup: Scribble-supervised convolutional networks for semantic segmentation,
D. Lin, J. Dai, J. Jia, K. He, J. Sun, · 2016
Cited alongside, same era.
Learning to refine object segments,
P. O. Pinheiro, T.-Y. Lin, R. Collobert, P. Dollár, · 2016
Cited alongside, same era.
A benchmark dataset and evaluation methodology for video object segmentation,
F. Perazzi, J. Pont-Tuset, B. McWilliams, L. V. Gool, M. Gross, A. Sorkine-Hornung, · 2016
Cited alongside, same era.
Optimizing intersection-over-union in deep neural networks for image segmentation,
M. A. Rahman, Y. Wang, · 2016
Cited alongside, same era.
Regional interactive image segmentation networks,
J. Liew, Y. Wei, W. Xiong, S.-H. Ong, J. Feng, · 2017
Cited alongside, same era.
DeepLab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected CRFs,
MultiSeg: Semantically meaningful, scale-diverse segmentations from minimal user input,
J. H. Liew, S. Cohen, B. Price, L. Mai, S.-H. Ong, J. Feng, · 2019
Later among the works it cites.
Content-aware multi-level guidance for interactive instance segmentation,
S. Majumder, A. Yao, · 2019
Later among the works it cites.
AdaptIS: Adaptive instance selection network,
K. Sofiiuk, O. Barinova, A. Konushin, O. Barinova, · 2019
Later among the works it cites.
Pytorch: An imperative style, high-performance deep learning library,
A. Paszke, S. Gross, F. Massa, A. Lerer, J. Bradbury, G. Chanan, T. Killeen, Z. Lin, N. Gimelshein, L. Antiga, A. Desmaison, A. Köpf, E. Yang, Z. DeVito, M. Raison, A. Tejani, S. Chilamkurthy, B. Steiner, L. Fang, J. Bai, S. Chintala, · 2019
Later among the works it cites.
Continuous adaptation for interactive object segmentation by learning from corrections,
T. Kontogianni, M. Gygli, J. Uijlings, V. Ferrari, · 2020
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L.-C. Chen, G. Papandreou, I. Kokkinos, K. Murphy, A. L. Yuille, · 2017
Cited alongside, same era.
Focal loss for dense object detection,
T.-Y. Lin, P. Goyal, R. Girshick, K. He, P. Dollár, · 2017
Cited alongside, same era.
Scene parsing through ADE20k dataset,
B. Zhou, H. Zhao, X. Puig, S. Fidler, A. Barriuso, A. Torralba, · 2017
Cited alongside, same era.
Deep extreme cut: From extreme points to object segmentation,
K.-K. Maninis, S. Caelles, J. Pont-Tuset, L. V. Gool, · 2018
Cited alongside, same era.
Efficient interactive annotation of segmentation datasets with polygon-RNN + + ++ ,
D. Acuna, H. Ling, A. Kar, S. Fidler, · 2018
Cited alongside, same era.
Iteratively trained interactive segmentation,
S. Mahadevan, P. Voigtlaender, B. Leibe, · 2018
Cited alongside, same era.
Interactive image segmentation with latent diversity,
Z. Li, Q. Chen, V. Koltun, · 2018
Cited alongside, same era.
F-BRS: Rethinking backpropagating refinement for interactive segmentation,
K. Sofiiuk, I. Petrov, O. Barinova, A. Konushin, · 2020
Later among the works it cites.
Interactive image segmentation with first click attention,
Z. Lin, Z. Zhang, L.-Z. Chen, M.-M. Cheng, S.-P. Lu, · 2020
Later among the works it cites.
Interactive object segmentation with inside-outside guidance,
S. Zhang, J. H. Liew, Y. Wei, S. Wei, Y. Zhao, · 2020
Later among the works it cites.
PhraseClick: Toward achieving flexible interactive segmentation by phrase and click,
H. Ding, S. Cohen, B. Price, X. Jiang, · 2020
Later among the works it cites.
SegFix: Model-agnostic boundary refinement for segmentation,
Y. Yuan, J. Xie, X. Chen, J. Wang, · 2020
Later among the works it cites.
Deepstrip: High-resolution boundary refinement,
P. Zhou, B. Price, S. Cohen, G. Wilensky, L. S. Davis, · 2020
Later among the works it cites.
Deep high-resolution representation learning for visual recognition,
J. Wang, K. Sun, T. Cheng, B. Jiang, C. Deng, Y. Zhao, D. Liu, Y. Mu, M. Tan, X. Wang, W. Liu, B. Xiao, · 2020
Later among the works it cites.
Object-contextual representations for semantic segmentation,
Y. Yuan, X. Chen, J. Wang, · 2020
Later among the works it cites.
Learning to segment the tail,
X. Hu, Y. Jiang, K. Tang, J. Chen, C. Miao, H. Zhang, · 2020
Later among the works it cites.
Balanced meta-softmax for long-tailed visual recognition,
R. Jiawei, C. Yu, X. Ma, H. Zhao, S. Yi, et al., · 2020
Later among the works it cites.
Equalization loss for long-tailed object recognition,
J. Tan, C. Wang, B. Li, Q. Li, W. Ouyang, C. Yin, J. Yan, · 2020
Later among the works it cites.
Solov2: Dynamic and fast instance segmentation,
X. Wang, R. Zhang, T. Kong, L. Li, C. Shen, · 2020
Later among the works it cites.