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The prevailing paradigm for producing semantic segmentation training data relies on densely labelling each pixel of each image in the training set, akin to colouring-in books.
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Learning generative visual models from few training examples: An incremental bayesian approach tested on 101 object categories
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Learning to detect natural image boundaries using local brightness, color, and texture cues
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TextonBoost: Joint appearance, shape and context modeling for multi-class object recognition and segmentation
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LabelMe: A database and web-based tool for image annotation
B. C. Russell, A. Torralba, K. P. Murphy, and W. T. Freeman · 2008
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Multi-class active learning for image classification
Ajay J Joshi, Fatih Porikli, and Nikolaos Papanikolopoulos · 2009
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Active learning literature survey
Burr Settles · 2009
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TextonBoost for image understanding: Multi-class object recognition and segmentation by jointly modeling appearance, shape and context
J. Shotton, J. Winn, C. Rother, and A. Criminisi · 2009
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iCoseg: Interactive co-segmentation with intelligent scribble guidance
D. Batra, A. Kowdle, D. Parikh, J. Luo, and T. Chen · 2010
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What does classifying more than 10,000 image categories tell us?
J. Deng, A. C. Berg, K. Li, and L. Fei-Fei · 2010
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The multidimensional wisdom of crowds
Peter Welinder, Steve Branson, Pietro Perona, and Serge J Belongie · 2010
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Crowdclustering
Ryan G. Gomes, Peter Welinder, Andreas Krause, and Pietro Perona · 2011
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Semantic contours from inverse detectors
B. Hariharan, P. Arbeláez, L. Bourdev, S. Maji, and J. Malik · 2011
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Relative attributes
Devi Parikh and Kristen Grauman · 2011
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The PASCAL Visual Object Classes Challenge 2012 (VOC2012) Results
M. Everingham, L. Van Gool, C. K. I. Williams, J. Winn, and A. Zisserman · 2012
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Active learning for semantic segmentation with expected change
A. Vezhnevets, J. M. Buhmann, and V. Ferrari · 2012
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Covida: pen-based collaborative video annotation
Tobias Zimmermann, Markus Weber, Marcus Liwicki, and Didier Stricker · 2012
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What is a good evaluation measure for semantic segmentation?
G. Csurka, D. Larlus, and Perronnin F · 2013
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Composite statistical inference for semantic segmentation
F. Li, J. Carreira, G. Lebanon, and C. Sminchisescu · 2013
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Scalable multi-label annotation
Jia Deng, Olga Russakovsky, Jonathan Krause, Michael S. Bernstein, Alex Berg, and Li Fei-Fei · 2014
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Learning everything about anything: Webly-supervised visual concept learning
S. Divvala, A. Farhadi, and C. Guestrin · 2014
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Microsoft COCO: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge Belongie, Lubomir Bourdev, Ross Girshick, James Hays, Pietro Perona, Deva Ramanan, C. Lawrence Zitnick, and Piotr Dollár · 2014
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How many visual concepts?
John R Smith · 2014
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Densecut: Densely connected crfs for realtime grabcut
Ming-Ming Cheng, V A Prisacariu, Shuai Zheng, Philip H. S. Torr, and Carsten Rother · 2015
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Boxsup: Exploiting bounding boxes to supervise convolutional networks for semantic segmentation
Jifeng Dai, Kaiming He, and Jian Sun · 2015
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The PASCAL visual object classes challenge: A retrospective
M. Everingham, S. Eslami, L. van Gool, C. Williams, J. Winn, and A. Zisserman · 2015
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Weakly- and semi-supervised learning of a deep convolutional network for semantic image segmentation
G. Papandreou, L.-C. Chen, K. Murphy, and A. L. Yuille · 2015
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Constrained convolutional neural networks for weakly supervised segmentation
D. Pathak, P. Krähenbühl, and T. Darrell · 2015
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Supervised evaluation of image segmentation and object proposal techniques
Jordi Pont-Tuset and Ferran Marques · 2015
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ImageNet large scale visual recognition challenge
O. Russakovsky, J. Deng, H. Su, J. Krause, S. Satheesh, S. Ma, Z. Huang, A. Karpathy, A. Khosla, M. Bernstein, A. Berg, and L. Fei-Fei · 2015
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What’s the point: Semantic segmentation with point supervision
A. Bearman, O. Russakovsky, V. Ferrari, and L. Fei-Fei · 2016
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Single-image depth perception in the wild
W. Chen, Z. Fu, D. Yang, and J. Deng · 2016
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The cityscapes dataset for semantic urban scene understanding
M. Cordts, M. Omran, S. Ramos, T. Rehfeld, M. Enzweiler, R. Benenson, U. Franke, S. Roth, and B. Schiele · 2016
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Active image segmentation propagation
Suyog Dutt Jain and Kristen Grauman · 2016
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Seed, expand and constrain: Three principles for weakly-supervised image segmentation
A. Kolesnikov and C.H. Lampert · 2016
Efficient object annotation via speaking and pointing
Michael Gygli and Vittorio Ferrari · 2019
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Panoptic segmentation
A. Kirillov, K. He, R. Girshick, C. Rother, and P. Dollar · 2019
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Instance segmentation with point supervision
Issam H Laradji, Negar Rostamzadeh, Pedro O Pinheiro, David Vázquez, and Mark Schmidt · 2019
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Visualbert: A simple and performant baseline for vision and language
Liunian Harold Li, Mark Yatskar, Da Yin, Cho-Jui Hsieh, and Kai-Wei Chang · 2019
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Block annotation: Better image annotation with sub-image decomposition
Hubert Lin, Paul Upchurch, and Kavita Bala · 2019
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Crowdsourcing in computer vision
Adriana Kovashka, Olga Russakovsky, Li Fei-Fei, and Kristen Grauman · 2016
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ScribbleSup: Scribble-supervised convolutional networks for semantic segmentation
D. Lin, J. Dai, J. Jia, K. He, and J. Sun · 2016
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Deep interactive object selection
N. Xu, B. Price, S. Cohen, J. Yang, and T.S. Huang · 2016
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Webly supervised semantic segmentation
B. Jin, M.V. Ortiz-Segovia, and S. Süsstrunk · 2017
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Simple does it: Weakly supervised instance and semantic segmentation
A. Khoreva, R. Benenson, J. Hosang, M. Hein, and B. Schiele · 2017
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Exploiting saliency for object segmentation from image level labels
S. Oh, R. Benenson, A. Khoreva, Z. Akata, M. Fritz, and B. Schiele · 2017
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Vilbert: Pretraining task-agnostic visiolinguistic representations for vision-and-language tasks
Jiasen Lu, Dhruv Batra, Devi Parikh, and Stefan Lee · 2019
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Industry-scale knowledge graphs: lessons and challenges
Natasha Noy, Yuqing Gao, Anshu Jain, Anant Narayanan, Alan Patterson, and Jamie Taylor · 2019
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Natural vocabulary emerges from free-form annotations
Jordi Pont-Tuset, Michael Gygli, and Vittorio Ferrari · 2019
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Variational adversarial active learning
Samarth Sinha, Sayna Ebrahimi, and Trevor Darrell · 2019
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Vl-bert: Pre-training of generic visual-linguistic representations
Weijie Su, Xizhou Zhu, Yue Cao, Bin Li, Lewei Lu, Furu Wei, and Jifeng Dai · 2019
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Semantic understanding of scenes through the ADE20K dataset
B. Zhou, H. Zhao, X. Puig, S. Fidler, A. Barriuso, and A. Torralba · 2019
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A simple framework for contrastive learning of visual representations
Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton · 2020
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The open images dataset v4: Unified image classification, object detection, and visual relationship detection at scale
Alina Kuznetsova, Hassan Rom, Neil Alldrin, Jasper Uijlings, Ivan Krasin, Jordi Pont-Tuset, Shahab Kamali, Stefan Popov, Matteo Malloci, Alexander Kolesnikov, Tom Duerig, and Vittorio Ferrari · 2020
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Fss-1000: A 1000-class dataset for few-shot segmentation
Xiang Li, Tianhan Wei, Yau Pun Chen, Yu-Wing Tai, and Chi-Keung Tang · 2020
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Oscar: Object-semantics aligned pre-training for vision-language tasks
Xiujun Li, Xi Yin, Chunyuan Li, Pengchuan Zhang, Xiaowei Hu, Lei Zhang, Lijuan Wang, Houdong Hu, Li Dong, Furu Wei, et al · 2020
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Pcams: Weakly supervised semantic segmentation using point supervision
R Austin McEver and BS Manjunath · 2020
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Self-supervised learning of pretext-invariant representations
Ishan Misra and Laurens van der Maaten · 2020
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Connecting vision and language with localized narratives
Jordi Pont-Tuset, Jasper Uijlings, Soravit Changpinyo, Radu Soricut, and Vittorio Ferrari · 2020
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Self-supervised equivariant attention mechanism for weakly supervised semantic segmentation
Yude Wang, Jie Zhang, Meina Kan, Shiguang Shan, and Xilin Chen · 2020
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Emerging properties in self-supervised vision transformers
Mathilde Caron, Hugo Touvron, Ishan Misra, Hervé Jégou, Julien Mairal, Piotr Bojanowski, and Armand Joulin · 2021
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Scaling open-vocabulary image segmentation with image-level labels
Golnaz Ghiasi, Xiuye Gu, Yin Cui, and Tsung-Yi Lin · 2021
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Scaling up visual and vision-language representation learning with noisy text supervision
Chao Jia, Yinfei Yang, Ye Xia, Yi-Ting Chen, Zarana Parekh, Hieu Pham, Quoc Le, Yun-Hsuan Sung, Zhen Li, and Tom Duerig · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
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All you need are a few pixels: semantic segmentation with pixelpick
Gyungin Shin, Weidi Xie, and Samuel Albanie · 2021
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Semantic segmentation in-the-wild without seeing any segmentation examples
Nir Zabari and Yedid Hoshen · 2021
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Pointly-supervised instance segmentation
Bowen Cheng, Omkar Parkhi, and Alexander Kirillov · 2022
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Decoupling zero-shot semantic segmentation
Jian Ding, Nan Xue, Guisong Xia, and Dengxin Dai · 2022
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Image segmentation using text and image prompts
Timo Lüddecke and Alexander S. Ecker · 2022
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Active pointly-supervised instance segmentation
Chufeng Tang, Lingxi Xie, Gang Zhang, Xiaopeng Zhang, Qi Tian, and Xiaolin Hu · 2022
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Cris: Clip-driven referring image segmentation
Zhaoqing Wang, Yu Lu, Qiang Li, Xunqiang Tao, Yandong Guo, Mingming Gong, and Tongliang Liu · 2022
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