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Unconditional scene inference and generation are challenging to learn jointly with a single compositional model.
Spatial broadcast decoder: A simple architecture for learning disentangled representations in vaes
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Neural autoregressive distribution estimation
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GANs trained by a two time-scale update rule converge to a local nash equilibrium
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Learning object-centric representations of multi-object scenes from multiple views
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SPACE: unsupervised object-oriented scene representation via spatial attention and decomposition
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Attention is all you need
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Shapestacks: Learning vision-based physical intuition for generalised object stacking
Oliver Groth, Fabian B Fuchs, Ingmar Posner, and Andrea Vedaldi · 2018
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Learning latent permutations with gumbel-sinkhorn networks
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Towards causal generative scene models via competition of experts
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Unsupervised object-based transition models for 3d partially observable environments
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Generative scene graph networks
Fei Deng, Zhuo Zhi, Donghun Lee, and Sungjin Ahn · 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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GENESIS-V2: Inferring unordered object representations without iterative refinement
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Set-to-sequence methods in machine learning: a review
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SIMONe: View-invariant, temporally-abstracted object representations via unsupervised video decomposition
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Discovering non-monotonic autoregressive orderings with variational inference
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Toward causal representation learning
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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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Unsupervised discovery of object radiance fields
Hong-Xing Yu, Leonidas J Guibas, and Jiajun Wu · 2021
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Unsupervised learning of compositional scene representations from multiple unspecified viewpoints
Jinyang Yuan, Bin Li, and Xiangyang Xue · 2021
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PROVIDE: a probabilistic framework for unsupervised video decomposition
Polina Zablotskaia, Edoardo A Dominici, Leonid Sigal, and Andreas M Lehrmann · 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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Dall·e 2 preview - risks and limitations
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