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We follow the idea of formulating vision as inverse graphics and propose a new type of element for this task, a neural-symbolic capsule.
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Sabour, S., Frosst, N., Hinton, G.E.: Dynamic routing between capsules. NIPS (2017)
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Liu, Z., Freeman, W.T., Tenenbaum, J.B., Wu, J.: Physical primitive decomposition. ECCV (2018)
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Yao, S., Hsu, T.M.H., Zhu, J.Y., Wu, J., Torralba, A., Freeman, W.T., Tenenbaum, J.B.: 3d-aware scene manipulation via inverse graphics. NIPS (2018)
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Yi, K., Wu, J., Gan, C., Torralba, A., Kohli, P., Tenenbaum, J.B.: Neural-symbolic vqa: Disentangling reasoning from vision and language understanding. NIPS (2018)
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Tulsiani, S., Su, H., Guibas, L.J., Efros, A.A., Malik, J.: Learning shape abstractions by assembling volumetric primitives. CVPR (2017)
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Ullman, T.D., Spelke, E., Battaglia, P., Tenenbaum, J.B.: Mind games: Game engines as an architecture for intuitive physics. Trends in Cognitive Science 21
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Wu, J., Tenenbaum, J.B., Kohli, P.: Neural scene de-rendering. CVPR (2017)
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Zou, C., Yumer, E., Yang, J., Ceylan, D., Hoiem, D.: 3d-prnn: Generating shape primitives with recurrent neural networks. ICCV (2017)
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Hinton, G.E., Sabour, S., Frosst, N.: Matrix capsules with EM routing. ICLR (2018)
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Lenssen, J.E., Fey, M., Libuschewski, P.: Group equivariant capsule networks. NIPS (2018)
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Zhao, Y., Birdal, T., Deng, H., Tombari, F.: 3d point-capsule networks. arXiv:1812.10775 (2018)
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Zhou, Y., Zhu, Z., Bai, X., Lischinski, D., Cohen-Or, D., Huang, H.: Non-stationary texture synthesis by adversarial expansion. SIGGRAPH (2018)
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Liu, Y., Wu, Z., Ritchie, D., Freeman, W.T., Tenenbaum, J.B., Wu, J.: Learning to describe scenes with programs. ICLR (2019)
2019
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Mao, J., Gan, C., Kohli, P., Tenenbaum, J.B., Wu, J.: The neuro-symbolic concept learner: Interpreting scenes, words, and sentences from natural supervision. ICLR (2019)
2019
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Team, G.E.: Godot engine (2019), https://godotengine.org
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Tian, Y., Luo, A., Sun, X., Ellis, K., Freeman, W.T., Tenenbaum, J.B., Wu, J.: Learning to infer and execute 3d shape programs. ICLR (2019)
2019
Closest in time.