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Current state-of-the-art object-centric models use slots and attention-based routing for binding.
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Klaus Greff, Sjoerd van Steenkiste, and Jürgen Schmidhuber · 2017
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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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On the binding problem in artificial neural networks
Klaus Greff, Sjoerd van Steenkiste, and Jürgen Schmidhuber · 2020
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Learning object-centric video models by contrasting sets
Sindy Löwe, Klaus Greff, Rico Jonschkowski, Alexey Dosovitskiy, and Thomas Kipf · 2020
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Attention over learned object embeddings enables complex visual reasoning
David Ding, Felix Hill, Adam Santoro, Malcolm Reynolds, and Matthew Botvinick · 2021
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Unsupervised object keypoint learning using local spatial predictability
Anand Gopalakrishnan, Sjoerd van Steenkiste, and Jürgen Schmidhuber · 2021
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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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Relational neural expectation maximization: Unsupervised discovery of objects and their interactions
Sjoerd van Steenkiste, Michael Chang, Klaus Greff, and Jürgen Schmidhuber · 2018
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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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Representation learning with contrastive predictive coding
Aaron van den Oord, Yazhe Li, and Oriol Vinyals · 2018
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Matrix capsules with EM routing
Geoffrey E Hinton, Sara Sabour, and Nicholas Frosst · 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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Learning dexterous grasping with object-centric visual affordances
Priyanka Mandikal and Kristen Grauman · 2021
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Apex: Unsupervised, object-centric scene segmentation and tracking for robot manipulation
Yizhe Wu, Oiwi Parker Jones, Martin Engelcke, and Ingmar Posner · 2021
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Generalizing object-centric task-axes controllers using keypoints
Mohit Sharma and Oliver Kroemer · 2021
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Linear transformers are secretly fast weight programmers
Imanol Schlag, Kazuki Irie, and Jürgen Schmidhuber · 2021
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Efficient iterative amortized inference for learning symmetric and disentangled multi-object representations
Patrick Emami, Pan He, Sanjay Ranka, and Anand Rangarajan · 2021
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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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Illiterate DALLE learns to compose
Gautam Singh, Fei Deng, and Sungjin Ahn · 2022
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SAVi++: Towards end-to-end object-centric learning from real-world videos
Gamaleldin F. Elsayed, Aravindh Mahendran, Sjoerd van Steenkiste, Klaus Greff, Michael C. Mozer, and Thomas Kipf · 2022
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Learning to generalize with object-centric agents in the open world survival game crafter
Aleksandar Stanić, Yujin Tang, David Ha, and Jürgen Schmidhuber · 2022
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Complex-valued autoencoders for object discovery
Sindy Löwe, Phillip Lippe, Maja Rudolph, and Max Welling · 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, Thomas Kipf, Abhijit Kundu, Dmitry Lagun, Issam Laradji, Hsueh-Ti (Derek) Liu, Henning Meyer, Yishu Miao, Derek Nowrouzezahrai, Cengiz Oztireli, Etienne Pot, Noha Radwan, Daniel Rebain, Sara Sabour, Mehdi S. M. Sajjadi, Matan Sela, Vincent Sitzmann, Austin Stone, Deqing Sun, Suhani Vora, Ziyu Wang, Tianhao Wu, Kwang Moo Yi, Fangcheng Zhong, and Andrea Tagliasacchi · 2022
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Towards self-supervised learning of global and object-centric representations
Federico Baldassarre and Hossein Azizpour · 2022
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Object discovery and representation networks
Olivier J Hénaff, Skanda Koppula, Evan Shelhamer, Daniel Zoran, Andrew Jaegle, Andrew Zisserman, João Carreira, and Relja Arandjelović · 2022
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Slotformer: Unsupervised visual dynamics simulation with object-centric models
Ziyi Wu, Nikita Dvornik, Klaus Greff, Thomas Kipf, and Animesh Garg · 2023
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An investigation into pre-training object-centric representations for reinforcement learning
Jaesik Yoon, Yi-Fu Wu, Heechul Bae, and Sungjin Ahn · 2023
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Rotating features for object discovery
Sindy Löwe, Phillip Lippe, Francesco Locatello, and Max Welling · 2023
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