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This paper studies the problem of object discovery -- separating objects from the background without manual labels.
Cats reared in stroboscopic illumination: Effects on receptive fields in visual cortex
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Principles of object perception
Elizabeth S Spelke · 1990
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The reviewing of object files: Object-specific integration of information
Daniel Kahneman, Anne Treisman, and Brian J Gibbs · 1992
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Efficient graph-based image segmentation
Pedro F Felzenszwalb and Daniel P Huttenlocher · 2004
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Core knowledge
Elizabeth S Spelke and Katherine D Kinzler · 2007
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ImageNet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Object segmentation by long term analysis of point trajectories
Thomas Brox and Jitendra Malik · 2010
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Are we ready for autonomous driving? The KITTI vision benchmark suite
Andreas Geiger, Philip Lenz, and Raquel Urtasun · 2012
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Higher order motion models and spectral clustering
Peter Ochs and Thomas Brox · 2012
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Learning object class detectors from weakly annotated video
Alessandro Prest, Christian Leistner, Javier Civera, Cordelia Schmid, and Vittorio Ferrari · 2012
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Principles of Gestalt psychology
Kurt Koffka · 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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Multiscale combinatorial grouping
Pablo Arbeláez, Jordi Pont-Tuset, Jonathan T Barron, Ferran Marques, and Jitendra Malik · 2014
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Learning phrase representations using rnn encoder-decoder for statistical machine translation
Kyunghyun Cho, Bart Van Merriënboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio · 2014
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Auto-encoding variational bayes
Diederik P Kingma and Max Welling · 2014
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Stochastic backpropagation and approximate inference in deep generative models
Danilo Jimenez Rezende, Shakir Mohamed, and Daan Wierstra · 2014
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Learning to see by moving
Pulkit Agrawal, Joao Carreira, and Jitendra Malik · 2015
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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
Diederik P Kingma and Jimmy Ba · 2015
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Faster R-CNN: Towards real-time object detection with region proposal networks
Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun · 2015
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Delving deeper into convolutional networks for learning video representations
Nicolas Ballas, Li Yao, Chris Pal, and Aaron Courville · 2016
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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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Identity mappings in deep residual networks
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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A large dataset to train convolutional networks for disparity, optical flow, and scene flow estimation
Nikolaus Mayer, Eddy Ilg, Philip Hausser, Philipp Fischer, Daniel Cremers, Alexey Dosovitskiy, and Thomas Brox · 2016
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End-to-end people detection in crowded scenes
Russell Stewart, Mykhaylo Andriluka, and Andrew Y Ng · 2016
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Weakly-supervised semantic segmentation using motion cues
Pavel Tokmakov, Karteek Alahari, and Cordelia Schmid · 2016
Cited alongside, same era.
End-to-end object detection with transformers
Nicolas Carion, Francisco Massa, Gabriel Synnaeve, Nicolas Usunier, Alexander Kirillov, and Sergey Zagoruyko · 2020
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GENESIS: Generative scene inference and sampling with object-centric latent representations
Martin Engelcke, Adam R Kosiorek, Oiwi Parker Jones, and Ingmar Posner · 2020
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CATER: A diagnostic dataset for compositional actions and temporal reasoning
Rohit Girdhar and Deva Ramanan · 2020
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Unsupervised object-centric video generation and decomposition in 3D
Paul Henderson and Christoph H Lampert · 2020
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SCALOR: Generative world models with scalable object representations
Jindong Jiang, Sepehr Janghorbani, Gerard De Melo, and Sungjin Ahn · 2020
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Decoupling representation and classifier for long-tailed recognition
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Priya Goyal, Piotr Dollár, Ross Girshick, Pieter Noordhuis, Lukasz Wesolowski, Aapo Kyrola, Andrew Tulloch, Yangqing Jia, and Kaiming He · 2017
Cited alongside, same era.
Mask R-CNN
Kaiming He, Georgia Gkioxari, Piotr Dollár, and Ross Girshick · 2017
Cited alongside, same era.
Weakly supervised semantic segmentation using web-crawled videos
Seunghoon Hong, Donghun Yeo, Suha Kwak, Honglak Lee, and Bohyung Han · 2017
Cited alongside, same era.
Flownet 2.0: Evolution of optical flow estimation with deep networks
Eddy Ilg, Nikolaus Mayer, Tonmoy Saikia, Margret Keuper, Alexey Dosovitskiy, and Thomas Brox · 2017
Cited alongside, same era.
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
Cited alongside, same era.
Learning features by watching objects move
Deepak Pathak, Ross Girshick, Piotr Dollár, Trevor Darrell, and Bharath Hariharan · 2017
Cited alongside, same era.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
Cited alongside, same era.
Bingyi Kang, Saining Xie, Marcus Rohrbach, Zhicheng Yan, Albert Gordo, Jiashi Feng, and Yannis Kalantidis · 2020
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Space: Unsupervised object-oriented scene representation via spatial attention and decomposition
Zhixuan Lin, Yi-Fu Wu, Skand Vishwanath Peri, Weihao Sun, Gautam Singh, Fei Deng, Jindong Jiang, and Sungjin Ahn · 2020
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Object-centric learning with slot attention
Francesco Locatello, Dirk Weissenborn, Thomas Unterthiner, Aravindh Mahendran, Georg Heigold, Jakob Uszkoreit, Alexey Dosovitskiy, and Thomas Kipf · 2020
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RAFT: Recurrent all-pairs field transforms for optical flow
Zachary Teed and Jia Deng · 2020
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Entity abstraction in visual model-based reinforcement learning
Rishi Veerapaneni, John D Co-Reyes, Michael Chang, Michael Janner, Chelsea Finn, Jiajun Wu, Joshua Tenenbaum, and Sergey Levine · 2020
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https://paralleldomain.com/ , November 2021
Parallel domain · 2021
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Image-level or object-level? A tale of two resampling strategies for long-tailed detection
Nadine Chang, Zhiding Yu, Yu-Xiong Wang, Anima Anandkumar, Sanja Fidler, and Jose M Alvarez · 2021
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Roots: Object-centric representation and rendering of 3D scenes
Chang Chen, Fei Deng, and Sungjin Ahn · 2021
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Exploring simple siamese representation learning
Xinlei Chen and Kaiming He · 2021
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Unsupervised discovery of 3D physical objects from video
Yilun Du, Kevin Smith, Tomer Ulman, Joshua Tenenbaum, and Jiajun Wu · 2021
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Distributional robustness loss for long-tail learning
Dvir Samuel and Gal Chechik · 2021
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Decomposing 3D scenes into objects via unsupervised volume segmentation
Karl Stelzner, Kristian Kersting, and Adam R Kosiorek · 2021
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SMURF: Self-teaching multi-frame unsupervised RAFT with full-image warping
Austin Stone, Daniel Maurer, Alper Ayvaci, Anelia Angelova, and Rico Jonschkowski · 2021
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Unsupervised object learning via common fate
Matthias Tangemann, Steffen Schneider, Julius von Kügelgen, Francesco Locatello, Peter Gehler, Thomas Brox, Matthias Kümmerer, Matthias Bethge, and Bernhard Schölkopf · 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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DyStaB: Unsupervised object segmentation via dynamic-static bootstrapping
Yanchao Yang, Brian Lai, and Stefano Soatto · 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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VideoLT: Large-scale long-tailed video recognition
Xing Zhang, Zuxuan Wu, Zejia Weng, Huazhu Fu, Jingjing Chen, Yu-Gang Jiang, and Larry Davis · 2021
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