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The evolution of 3D generative modeling has been notably propelled by the adoption of 2D diffusion models.
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Achlioptas, P., Diamanti, O., Mitliagkas, I., Guibas, L.: Learning representations and generative models for 3d point clouds. In: International conference on machine learning. pp. 40–49. PMLR (2018)
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Bao, F., Li, C., Zhu, J., Zhang, B.: Analytic-DPM: an analytic estimate of the optimal reverse variance in diffusion probabilistic models. In: International Conference on Learning Representations (2022), https://openreview.net/forum?id=0xiJLKH-ufZ
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Liu, L., Ren, Y., Lin, Z., Zhao, Z.: Pseudo numerical methods for diffusion models on manifolds. In: International Conference on Learning Representations (2022), https://openreview.net/forum?id=PlKWVd2yBkY
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Lu, C., Zhou, Y., Bao, F., Chen, J., Li, C., Zhu, J.: Dpm-solver: A fast ode solver for diffusion probabilistic model sampling in around 10 steps. Advances in Neural Information Processing Systems 35
2022
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Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41
2022
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Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Trans. Graph. 41
2022
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2022
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Liu, R., Wu, R., Van Hoorick, B., Tokmakov, P., Zakharov, S., Vondrick, C.: Zero-1-to-3: Zero-shot one image to 3d object. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 9298–9309 (2023)
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Liu, R., Wu, R., Van Hoorick, B., Tokmakov, P., Zakharov, S., Vondrick, C.: Zero-1-to-3: Zero-shot one image to 3d object. In: Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV). pp. 9298–9309 (October 2023)
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2023
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Metzer, G., Richardson, E., Patashnik, O., Giryes, R., Cohen-Or, D.: Latent-nerf for shape-guided generation of 3d shapes and textures. In: 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). pp. 12663–12673. IEEE Computer Society, Los Alamitos, CA, USA (jun 2023). https://doi.org/10.1109/CVPR52729.2023.01218, https://doi.ieeecomputersociety.org/10.1109/CVPR52729.2023.01218
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2022
Cited alongside, same era.
Saharia, C., Chan, W., Saxena, S., Li, L., Whang, J., Denton, E.L., Ghasemipour, K., Gontijo Lopes, R., Karagol Ayan, B., Salimans, T., et al.: Photorealistic text-to-image diffusion models with deep language understanding. Advances in Neural Information Processing Systems 35
2022
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Salimans, T., Ho, J.: Progressive distillation for fast sampling of diffusion models. In: International Conference on Learning Representations (2022), https://openreview.net/forum?id=TIdIXIpzhoI
2022
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2023
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Chen, R., Chen, Y., Jiao, N., Jia, K.: Fantasia3d: Disentangling geometry and appearance for high-quality text-to-3d content creation. In: Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) (October 2023)
2023
Cited alongside, same era.
Chen, Y., Li, Z., Liu, P.: Et3d: Efficient text-to-3d generation via multi-view distillation (2023)
2023
Cited alongside, same era.
Fang, G., Ma, X., Wang, X.: Structural pruning for diffusion models. In: Advances in Neural Information Processing Systems (2023)
2023
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Girish, S., Shrivastava, A., Gupta, K.: Shacira: Scalable hash-grid compression for implicit neural representations. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 17513–17524 (2023)
2023
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2023
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Poole, B., Jain, A., Barron, J.T., Mildenhall, B.: Dreamfusion: Text-to-3d using 2d diffusion. In: The Eleventh International Conference on Learning Representations (2023), https://openreview.net/forum?id=FjNys5c7VyY
2023
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2023
Later among the works it cites.
2023
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Shue, J.R., Chan, E.R., Po, R., Ankner, Z., Wu, J., Wetzstein, G.: 3d neural field generation using triplane diffusion. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 20875–20886 (2023)
2023
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2023
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2023
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Wang, H., Du, X., Li, J., Yeh, R.A., Shakhnarovich, G.: Score jacobian chaining: Lifting pretrained 2d diffusion models for 3d generation. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 12619–12629 (2023)
2023
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Xie, X., Gherardi, R., Pan, Z., Huang, S.: Hollownerf: Pruning hashgrid-based nerfs with trainable collision mitigation. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 3480–3490 (2023)
2023
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Yang, X., Zhou, D., Feng, J., Wang, X.: Diffusion probabilistic model made slim. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 22552–22562 (2023)
2023
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2023
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2024
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Liu, M., Xu, C., Jin, H., Chen, L., Varma T, M., Xu, Z., Su, H.: One-2-3-45: Any single image to 3d mesh in 45 seconds without per-shape optimization. Advances in Neural Information Processing Systems 36
2024
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Liu, Y., Lin, C., Zeng, Z., Long, X., Liu, L., Komura, T., Wang, W.: Syncdreamer: Generating multiview-consistent images from a single-view image. In: The Twelfth International Conference on Learning Representations (2024), https://openreview.net/forum?id=MN3yH2ovHb
2024
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Qian, G., Mai, J., Hamdi, A., Ren, J., Siarohin, A., Li, B., Lee, H.Y., Skorokhodov, I., Wonka, P., Tulyakov, S., Ghanem, B.: Magic123: One image to high-quality 3d object generation using both 2d and 3d diffusion priors. In: The Twelfth International Conference on Learning Representations (ICLR) (2024), https://openreview.net/forum?id=0jHkUDyEO9
2024
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Wang, Z., Lu, C., Wang, Y., Bao, F., Li, C., Su, H., Zhu, J.: Prolificdreamer: High-fidelity and diverse text-to-3d generation with variational score distillation. Advances in Neural Information Processing Systems 36
2024
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2024
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