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Given an image of a natural scene, we are able to quickly decompose it into a set of components such as objects, lighting, shadows, and foreground.
Aspects of the Theory of Syntax
Chomsky, N · 1965
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A tutorial on energy-based learning
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Are we ready for autonomous driving? the kitti vision benchmark suite
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Deep unsupervised learning using nonequilibrium thermodynamics
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Chen, X., Duan, Y., Houthooft, R., Schulman, J., Sutskever, I., and Abbeel, P · 2016
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Unsupervised feature extraction by time-contrastive learning and nonlinear ica
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Gans trained by a two time-scale update rule converge to a local nash equilibrium
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Clevr: A diagnostic dataset for compositional language and elementary visual reasoning
Johnson, J., Hariharan, B., van der Maaten, L., Fei-Fei, L., Zitnick, C. L., and Girshick, R · 2017
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Progressive growing of gans for improved quality, stability, and variation
Karras, T., Aila, T., Laine, S., and Lehtinen, J · 2017
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Building machines that learn and think like people
Lake, B. M., Ullman, T. D., Tenenbaum, J. B., and Gershman, S. J · 2017
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Bińkowski, M., Sutherland, D. J., Arbel, M., and Gretton, A · 2018
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Understanding disentangling in beta-vae
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Isolating sources of disentanglement in variational autoencoders
Chen, T. Q., Li, X., Grosse, R., and Duvenaud, D · 2018
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Scan: Learning hierarchical compositional visual concepts
Higgins, I., Sonnerat, N., Matthey, L., Pal, A., Burgess, C. P., Bosnjak, M., Shanahan, M., Botvinick, M., Hassabis, D., and Lerchner, A · 2018
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Generative models of visually grounded imagination
Vedantam, R., Fischer, I., Huang, J., and Murphy, K · 2018
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The unreasonable effectiveness of deep networks as a perceptual metric
Zhang, R., Isola, P., Efros, A. A., Shechtman, E., and Wang, O · 2018
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Danbooru2019 portraits: A large-scale anime head illustration dataset, 2019
Branwen, G., Anonymous, and Community, D · 2019
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Monet: Unsupervised scene decomposition and representation
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Implicit generation and generalization in energy-based models
Du, Y. and Mordatch, I · 2019
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Multi-object representation learning with iterative variational inference
Greff, K., Kaufmann, R. L., Kabra, R., Watters, N., Burgess, C., Zoran, D., Matthey, L., Botvinick, M., and Lerchner, A · 2019
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Finegan: Unsupervised hierarchical disentanglement for fine-grained object generation and discovery
Singh, K. K., Ojha, U., and Lee, Y. J · 2019
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Rapid trial-and-error learning with simulation supports flexible tool use and physical reasoning
Allen, K. R., Smith, K. A., and Tenenbaum, J. B · 2020
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Cabon, Y., Murray, N., and Humenberger, M · 2020
Break-a-scene: Extracting multiple concepts from a single image
Avrahami, O., Aberman, K., Fried, O., Cohen-Or, D., and Lischinski, D · 2023
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The hidden language of diffusion models
Chefer, H., Lang, O., Geva, M., Polosukhin, V., Shocher, A., Irani, M., Mosseri, I., and Wolf, L · 2023
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Attribute-centric compositional text-to-image generation
Cong, Y., Min, M. R., Li, L. E., Rosenhahn, B., and Yang, M. Y · 2023
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Reduce, reuse, recycle: Compositional generation with energy-based diffusion models and mcmc
Du, Y., Durkan, C., Strudel, R., Tenenbaum, J. B., Dieleman, S., Fergus, R., Sohl-Dickstein, J., Doucet, A., and Grathwohl, W · 2023
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Compositional sculpting of iterative generative processes
Garipov, T., De Peuter, S., Yang, G., Garg, V., Kaski, S., and Jaakkola, T · 2023
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Denoising diffusion probabilistic models
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Peebles, W., Peebles, J., Zhu, J.-Y., Efros, A., and Torralba, A · 2020
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Towards nonlinear disentanglement in natural data with temporal sparse coding
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Learning to compose visual relations
Liu, N., Li, S., Du, Y., Tenenbaum, J., and Torralba, A · 2021
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Unsupervised layered image decomposition into object prototypes
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Object-centric slot diffusion, 2023
Jiang, J., Deng, F., Singh, G., and Ahn, S · 2023
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Multi-concept customization of text-to-image diffusion
Kumari, N., Zhang, B., Zhang, R., Shechtman, E., and Zhu, J.-Y · 2023
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Language-informed visual concept learning
Lee, S., Zhang, Y., Wu, S., and Wu, J · 2023
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Photomaker: Customizing realistic human photos via stacked id embedding
Li, Z., Cao, M., Wang, X., Qi, Z., Cheng, M.-M., and Shan, Y · 2023
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Referring image segmentation using text supervision
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Wei, Y., Zhang, Y., Ji, Z., Bai, J., Zhang, L., and Zuo, W · 2023
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Slotdiffusion: Object-centric generative modeling with diffusion models
Wu, Z., Hu, J., Lu, W., Gilitschenski, I., and Garg, A · 2023
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A simple framework for text-supervised semantic segmentation
Yi, M., Cui, Q., Wu, H., Yang, C., Yoshie, O., and Lu, H · 2023
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Unsupervised compositional concepts discovery with text-to-image generative models
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