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The recent success of transformer-based image generative models in object-centric learning highlights the importance of powerful image generators for handling complex scenes.
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SM Ali Eslami, Nicolas Heess, Theophane Weber, Yuval Tassa, David Szepesvari, and Geoffrey E Hinton · 2016
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Klaus Greff, Sjoerd van Steenkiste, and Jürgen Schmidhuber · 2017
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Tian Qi Chen, Xuechen Li, Roger B Grosse, and David K Duvenaud · 2018
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Hyunjik Kim and Andriy Mnih · 2018
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Object-centric image generation with factored depths, locations, and appearances
Titas Anciukevicius, Christoph H Lampert, and Paul Henderson · 2020
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Generative scene graph networks
Fei Deng, Zhuo Zhi, Donghun Lee, and Sungjin Ahn · 2020
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Unsupervised discovery of 3d physical objects from video
Yilun Du, Kevin Smith, Tomer Ulman, Joshua Tenenbaum, and Jiajun Wu · 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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Object-centric learning with slot attention, 2020
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Learning object-centric video models by contrasting sets
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Compositional Visual Generation with Composable Diffusion Models
Nan Liu, Shuang Li, Yilun Du, Antonio Torralba, and Joshua Tenenbaum · 2022
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Nan Liu, Shuang Li, Yilun Du, Antonio Torralba, and Joshua B Tenenbaum · 2022
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Complex-valued autoencoders for object discovery
Sindy Lowe, Phillip Lippe, Maja R. Rudolph, and Max Welling · 2022
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Sdedit: Guided Image Synthesis and Editing with Stochastic Differential Equations
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GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models
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Julius von Kügelgen, Ivan Ustyuzhaninov, Peter Gehler, Matthias Bethge, and Bernhard Schölkopf · 2020
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Diffusion models beat gans on image synthesis
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Unsupervised learning of compositional energy concepts
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Image Super-Resolution Via Iterative Refinement
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Object Scene Representation Transformer
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Bridging the gap to real-world object-centric learning
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Illiterate dall-e learns to compose
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Simple unsupervised object-centric learning for complex and naturalistic videos
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Unsupervised discovery and composition of object light fields
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Self-supervised visual representation learning with semantic grouping
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Robust and controllable object-centric learning through energy-based models
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