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Unsupervised multi-object segmentation has shown impressive results on images by utilizing powerful semantics learned from self-supervised pretraining.
Object segmentation by long term analysis of point trajectories
Thomas Brox and Jitendra Malik · 2010
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The pascal visual object classes (voc) challenge
Mark Everingham, Luc Van Gool, Christopher KI Williams, John Winn, and Andrew Zisserman · 2010
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Understanding the difficulty of training deep feedforward neural networks
Xavier Glorot and Yoshua Bengio · 2010
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Object segmentation in video: a hierarchical variational approach for turning point trajectories into dense regions
Peter Ochs and Thomas Brox · 2011
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Scikit-learn: Machine learning in Python
Fabian Pedregosa, Gaël Varoquaux, Alexandre Gramfort, Vincent Michel, Bertrand Thirion, Olivier Grisel, Mathieu Blondel, Peter Prettenhofer, Ron Weiss, Vincent Dubourg, Jake Vanderplas, Alexandre Passos, and David Cournapeau · 2011
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Video segmentation by tracing discontinuities in a trajectory embedding
Katerina Fragkiadaki, Geng Zhang, and Jianbo Shi · 2012
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Video segmentation by tracking many figure-ground segments
Fuxin Li, Taeyoung Kim, Ahmad Humayun, David Tsai, and James M Rehg · 2013
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Segmentation of moving objects by long term video analysis
Peter Ochs, Jitendra Malik, and Thomas Brox · 2013
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Fast object segmentation in unconstrained video
Anestis Papazoglou and Vittorio Ferrari · 2013
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Video segmentation by non-local consensus voting
Alon Faktor and Michal Irani · 2014
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Microsoft coco: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick · 2014
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Motion trajectory segmentation via minimum cost multicuts
Margret Keuper, Bjoern Andres, and Thomas Brox · 2015
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Adam: A method for stochastic optimization
Diederick P Kingma and Jimmy Ba · 2015
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Attend, infer, repeat: Fast scene understanding with generative models
SM Eslami, Nicolas Heess, Theophane Weber, Yuval Tassa, David Szepesvari, Geoffrey E Hinton, et al · 2016
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Tagger: Deep unsupervised perceptual grouping
Klaus Greff, Antti Rasmus, Mathias Berglund, Tele Hao, Harri Valpola, and Jürgen Schmidhuber · 2016
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A benchmark dataset and evaluation methodology for video object segmentation
Federico Perazzi, Jordi Pont-Tuset, Brian McWilliams, Luc Van Gool, Markus Gross, and Alexander Sorkine-Hornung · 2016
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Video segmentation via object flow
Yi-Hsuan Tsai, Ming-Hsuan Yang, and Michael J Black · 2016
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One-shot video object segmentation
Sergi Caelles, Kevis-Kokitsi Maninis, Jordi Pont-Tuset, Laura Leal-Taixe, Daniel Cremers, and Luc Van Gool · 2017
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Fusionseg: Learning to combine motion and appearance for fully automatic segmentation of generic objects in videos
Suyog Dutt Jain, Bo Xiong, and Kristen Grauman · 2017
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Shifting more attention to video salient object detection
Deng-Ping Fan, Wenguan Wang, Ming-Ming Cheng, and Jianbing Shen · 2017
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Neural expectation maximization
Klaus Greff, Sjoerd Van Steenkiste, and Jürgen Schmidhuber · 2017
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Clevr: A diagnostic dataset for compositional language and elementary visual reasoning
Justin Johnson, Bharath Hariharan, Laurens Van Der Maaten, Li Fei-Fei, C Lawrence Zitnick, and Ross Girshick · 2017
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Primary object segmentation in videos based on region augmentation and reduction
Yeong Jun Koh and Chang-Su Kim · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Sequential attend, infer, repeat: Generative modelling of moving objects
Adam Kosiorek, Hyunjik Kim, Yee Whye Teh, and Ingmar Posner · 2018
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Instance embedding transfer to unsupervised video object segmentation
Siyang Li, Bryan Seybold, Alexey Vorobyov, Alireza Fathi, Qin Huang, and C-C Jay Kuo · 2018
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Premvos: Proposal-generation, refinement and merging for video object segmentation
Jonathon Luiten, Paul Voigtlaender, and Bastian Leibe · 2018
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Video object segmentation without temporal information
K.-K. Maninis, S. Caelles, Y. Chen, J. Pont-Tuset, L. Leal-Taixé, D. Cremers, and L Van Gool · 2018
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Tracking emerges by colorizing videos
Carl Vondrick, Abhinav Shrivastava, Alireza Fathi, Sergio Guadarrama, and Kevin Murphy · 2018
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Youtube-vos: A large-scale video object segmentation benchmark
Ning Xu, Linjie Yang, Yuchen Fan, Dingcheng Yue, Yuchen Liang, Jianchao Yang, and Thomas Huang · 2018
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Monet: Unsupervised scene decomposition and representation
Christopher P Burgess, Loic Matthey, Nicholas Watters, Rishabh Kabra, Irina Higgins, Matt Botvinick, and Alexander Lerchner · 2019
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Spatially invariant unsupervised object detection with convolutional neural networks
Eric Crawford and Joelle Pineau · 2019
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Towards segmenting anything that moves
Achal Dave, Pavel Tokmakov, and Deva Ramanan · 2019
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Multi-object representation learning with iterative variational inference
Klaus Greff, Raphaël Lopez Kaufman, Rishabh Kabra, Nick Watters, Christopher Burgess, Daniel Zoran, Loic Matthey, Matthew Botvinick, and Alexander Lerchner · 2019
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Self-supervised learning for video correspondence flow
Zihang Lai and Weidi Xie · 2019
Cited alongside, same era.
See more, know more: Unsupervised video object segmentation with co-attention siamese networks
Clevrtex: A texture-rich benchmark for unsupervised multi-object segmentation
Laurynas Karazija, Iro Laina, and Christian Rupprecht · 2021
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Video instance segmentation with a propose-reduce paradigm
Huaijia Lin, Ruizheng Wu, Shu Liu, Jiangbo Lu, and Jiaya Jia · 2021
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The emergence of objectness: Learning zero-shot segmentation from videos
Runtao Liu, Zhirong Wu, Stella Yu, and Stephen Lin · 2021
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Giraffe: Representing scenes as compositional generative neural feature fields
Michael Niemeyer and Andreas Geiger · 2021
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Localizing objects with self-supervised transformers and no label
Oriane Siméoni, Gilles Puy, Huy V Vo, Simon Roburin, Spyros Gidaris, Andrei Bursuc, Patrick Pérez, Renaud Marlet, and Jean Ponce · 2021
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Large-scale unsupervised object discovery
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Xiankai Lu, Wenguan Wang, Chao Ma, Jianbing Shen, Ling Shao, and Fatih Porikli · 2019
Cited alongside, same era.
Video object segmentation using space-time memory networks
Seoung Wug Oh, Joon-Young Lee, Ning Xu, and Seon Joo Kim · 2019
Cited alongside, same era.
Faster attend-infer-repeat with tractable probabilistic models
Karl Stelzner, Robert Peharz, and Kristian Kersting · 2019
Cited alongside, same era.
Learning to segment moving objects
Pavel Tokmakov, Cordelia Schmid, and Karteek Alahari · 2019
Cited alongside, same era.
Feelvos: Fast end-to-end embedding learning for video object segmentation
Paul Voigtlaender, Yuning Chai, Florian Schroff, Hartwig Adam, Bastian Leibe, and Liang-Chieh Chen · 2019
Cited alongside, same era.
Spatial broadcast decoder: A simple architecture for learning disentangled representations in vaes
Nicholas Watters, Loic Matthey, Christopher P Burgess, and Alexander Lerchner · 2019
Cited alongside, same era.
Video instance segmentation
Linjie Yang, Yuchen Fan, and Ning Xu · 2019
Cited alongside, same era.
Van Huy Vo, Elena Sizikova, Cordelia Schmid, Patrick Pérez, and Jean Ponce · 2021
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Self-supervised video object segmentation by motion grouping
Charig Yang, Hala Lamdouar, Erika Lu, Andrew Zisserman, and Weidi Xie · 2021
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Unsupervised foreground extraction via deep region competition
Peiyu Yu, Sirui Xie, Xiaojian Ma, Yixin Zhu, Ying Nian Wu, and Song-Chun Zhu · 2021
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Parts: Unsupervised segmentation with slots, attention and independence maximization
Daniel Zoran, Rishabh Kabra, Alexander Lerchner, and Danilo J Rezende · 2021
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Discovering objects that can move
Zhipeng Bao, Pavel Tokmakov, Allan Jabri, Yu-Xiong Wang, Adrien Gaidon, and Martial Hebert · 2022
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A simple and powerful global optimization for unsupervised video object segmentation
Subhabrata Choudhury, Laurynas Karazija, Iro Laina, Andrea Vedaldi, and Christian Rupprecht · 2022
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Generalization and robustness implications in object-centric learning
Andrea Dittadi, Samuele Papa, Michele De Vita, Bernhard Schölkopf, Ole Winther, and Francesco Locatello · 2022
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Savi++: Towards end-to-end object-centric learning from real-world videos
Gamaleldin Elsayed, Aravindh Mahendran, Sjoerd van Steenkiste, Klaus Greff, Michael C Mozer, and Thomas Kipf · 2022
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Kubric: A scalable dataset generator
Klaus Greff, Francois Belletti, Lucas Beyer, Carl Doersch, Yilun Du, Daniel Duckworth, David J Fleet, Dan Gnanapragasam, Florian Golemo, Charles Herrmann, et al · 2022
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Masked autoencoders are scalable vision learners
Kaiming He, Xinlei Chen, Saining Xie, Yanghao Li, Piotr Dollár, and Ross Girshick · 2022
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Object discovery and representation networks
Hénaff, Olivier J and Koppula, Skanda and Shelhamer, Evan and Zoran, Daniel and Jaegle, Andrew and Zisserman, Andrew and Carreira, João and Arandjelović, Relja · 2022
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Unsupervised Multi-object Segmentation by Predicting Probable Motion Patterns
Laurynas Karazija, Subhabrata Choudhury, Iro Laina, Christian Rupprecht, and Andrea Vedaldi · 2022
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Conditional object-centric learning from video
Thomas Kipf, Gamaleldin F. Elsayed, Aravindh Mahendran, Sara Stone, Austinand Sabour, Georg Heigold, Rico Jonschkowski, Alexey Dosovitskiy, and Klaus Greff · 2022
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Deep spectral methods: A surprisingly strong baseline for unsupervised semantic segmentation and localization
Luke Melas-Kyriazi, Christian Rupprecht, Iro Laina, and Andrea Vedaldi · 2022
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A simple and powerful global optimization for unsupervised video object segmentation
Georgy Ponimatkin, Nermin Samet, Yang Xiao, Yuming Du, Renaud Marlet, and Vincent Lepetit · 2022
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Illiterate dall-e learns to compose
Gautam Singh, Fei Deng, and Sungjin Ahn · 2022
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Simple unsupervised object-centric learning for complex and naturalistic videos
Gautam Singh, Yi-Fu Wu, and Sungjin Ahn · 2022
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Self-supervised transformers for unsupervised object discovery using normalized cut
Yangtao Wang, Xi Shen, Shell Xu Hu, Yuan Yuan, James L Crowley, and Dominique Vaufreydaz · 2022
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Segmenting moving objects via an object-centric layered representation
Junyu Xie, Weidi Xie, and Andrew Zisserman · 2022
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Groupvit: Semantic segmentation emerges from text supervision
Jiarui Xu, Shalini De Mello, Sifei Liu, Wonmin Byeon, Thomas Breuel, Jan Kautz, and Xiaolong Wang · 2022
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Object discovery from motion-guided tokens
Zhipeng Bao, Pavel Tokmakov, Yu-Xiong Wang, Adrien Gaidon, and Martial Hebert · 2023
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Invariant slot attention: Object discovery with slot-centric reference frames
Ondrej Biza, Sjoerd van Steenkiste, Mehdi S. M. Sajjadi, Gamaleldin F. Elsayed, Aravindh Mahendran, and Thomas Kipf · 2023
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Dinov2: Learning robust visual features without supervision
Maxime Oquab, Timothée Darcet, Theo Moutakanni, Huy V. Vo, Marc Szafraniec, Vasil Khalidov, Pierre Fernandez, Daniel Haziza, Francisco Massa, Alaaeldin El-Nouby, Russell Howes, Po-Yao Huang, Hu Xu, Vasu Sharma, Shang-Wen Li, Wojciech Galuba, Mike Rabbat, Mido Assran, Nicolas Ballas, Gabriel Synnaeve, Ishan Misra, Herve Jegou, Julien Mairal, Patrick Labatut, Armand Joulin, and Piotr Bojanowski · 2023
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Bridging the gap to real-world object-centric learning
Maximilian Seitzer, Max Horn, Andrii Zadaianchuk, Dominik Zietlow, Tianjun Xiao, Carl-Johann Simon-Gabriel, Tong He, Zheng Zhang, Bernhard Schölkopf, Thomas Brox, et al · 2023
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Cut and learn for unsupervised object detection and instance segmentation
Xudong Wang, Rohit Girdhar, Stella X Yu, and Ishan Misra · 2023
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