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The recent 3D Gaussian splatting (3D-GS) has shown remarkable rendering fidelity and efficiency compared to NeRF-based neural scene representations.
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J. T. Barron, B. Mildenhall, M. Tancik, P. Hedman, R. Martin-Brualla, and P. P. Srinivasan, “Mip-nerf: A multiscale representation for anti-aliasing neural radiance fields,” in Proceedings of the IEEE/CVF International Conference on Computer Vision , 2021, pp. 5855–5864
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K. Park, U. Sinha, J. T. Barron, S. Bouaziz, D. B. Goldman, S. M. Seitz, and R. Martin-Brualla, “Nerfies: Deformable neural radiance fields,” in Proceedings of the IEEE/CVF International Conference on Computer Vision , 2021, pp. 5865–5874
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R. Martin-Brualla, N. Radwan, M. S. Sajjadi, J. T. Barron, A. Dosovitskiy, and D. Duckworth, “Nerf in the wild: Neural radiance fields for unconstrained photo collections,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2021, pp. 7210–7219
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J. T. Barron, B. Mildenhall, D. Verbin, P. P. Srinivasan, and P. Hedman, “Mip-nerf 360: Unbounded anti-aliased neural radiance fields,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2022, pp. 5470–5479
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2023
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Y. Xiangli, L. Xu, X. Pan, N. Zhao, A. Rao, C. Theobalt, B. Dai, and D. Lin, “Bungeenerf: Progressive neural radiance field for extreme multi-scale scene rendering,” in European conference on computer vision . Springer, 2022, pp. 106–122
2022
Cited alongside, same era.
M. Tancik, V. Casser, X. Yan, S. Pradhan, B. Mildenhall, P. P. Srinivasan, J. T. Barron, and H. Kretzschmar, “Block-nerf: Scalable large scene neural view synthesis,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2022, pp. 8248–8258
2022
Cited alongside, same era.
H. Turki, D. Ramanan, and M. Satyanarayanan, “Mega-nerf: Scalable construction of large-scale nerfs for virtual fly-throughs,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2022, pp. 12 922–12 931
2022
Cited alongside, same era.
L. Lin, Y. Liu, Y. Hu, X. Yan, K. Xie, and H. Huang, “Capturing, reconstructing, and simulating: the urbanscene3d dataset,” in European Conference on Computer Vision . Springer, 2022, pp. 93–109
2022
Cited alongside, same era.
Y. Li, L. Jiang, L. Xu, Y. Xiangli, Z. Wang, D. Lin, and B. Dai, “Matrixcity: A large-scale city dataset for city-scale neural rendering and beyond,” in Proceedings of the IEEE/CVF International Conference on Computer Vision , 2023, pp. 3205–3215
2023
Cited alongside, same era.
2023
Cited alongside, same era.
B. Kerbl, G. Kopanas, T. Leimkühler, and G. Drettakis, “3d gaussian splatting for real-time radiance field rendering,” ACM Transactions on Graphics , vol. 42, no. 4, 2023
2023
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2023
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S. Fridovich-Keil, G. Meanti, F. R. Warburg, B. Recht, and A. Kanazawa, “K-planes: Explicit radiance fields in space, time, and appearance,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2023, pp. 12 479–12 488
2023
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A. Cao and J. Johnson, “Hexplane: A fast representation for dynamic scenes,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2023, pp. 130–141
2023
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H. Bai, Y. Lin, Y. Chen, and L. Wang, “Dynamic plenoctree for adaptive sampling refinement in explicit nerf,” in Proceedings of the IEEE/CVF International Conference on Computer Vision , 2023, pp. 8785–8795
2023
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H. Hoppe, “Progressive meshes,” in Seminal Graphics Papers: Pushing the Boundaries, Volume 2 , 2023, pp. 111–120
2023
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B. Kerbl, A. Meuleman, G. Kopanas, M. Wimmer, A. Lanvin, and G. Drettakis, “A hierarchical 3d gaussian representation for real-time rendering of very large datasets,” ACM Transactions on Graphics (TOG) , vol. 43, no. 4, pp. 1–15, 2024
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B. Huang, Z. Yu, A. Chen, A. Geiger, and S. Gao, “2d gaussian splatting for geometrically accurate radiance fields,” in ACM SIGGRAPH 2024 Conference Papers , 2024, pp. 1–11
2024
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H. Turki, M. Zollhöfer, C. Richardt, and D. Ramanan, “Pynerf: Pyramidal neural radiance fields,” Advances in Neural Information Processing Systems , vol. 36, 2024
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