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In March 2020, Neural Radiance Field (NeRF) revolutionized Computer Vision, allowing for implicit, neural network-based scene representation and novel view synthesis.
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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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A. Jain, M. Tancik, and P. Abbeel, “Putting nerf on a diet: Semantically consistent few-shot view synthesis,” in Proceedings of the IEEE/CVF International Conference on Computer Vision , 2021, pp. 5885–5894
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E. Corona, T. Hodan, M. Vo, F. Moreno-Noguer, C. Sweeney, R. Newcombe, and L. Ma, “Lisa: Learning implicit shape and appearance of hands,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2022, pp. 20 533–20 543
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X. Long, C. Lin, P. Wang, T. Komura, and W. Wang, “Sparseneus: Fast generalizable neural surface reconstruction from sparse views,” in Computer Vision–ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23–27, 2022, Proceedings, Part XXXII . Springer, 2022, pp. 210–227
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2022
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K. Jo, G. Shim, S. Jung, S. Yang, and J. Choo, “Cg-nerf: Conditional generative neural radiance fields,” IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) , 2023
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L. Melas-Kyriazi, C. Rupprecht, I. Laina, and A. Vedaldi, “Realfusion: 360° reconstruction of any object from a single image,” arXiv e-prints , pp. arXiv–2302, 2023
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Z. Chen, T. Funkhouser, P. Hedman, and A. Tagliasacchi, “Mobilenerf: Exploiting the polygon rasterization pipeline for efficient neural field rendering on mobile architectures,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2023
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M. Zhang, S. Zheng, Z. Bao, M. Hebert, and Y.-X. Wang, “Beyond rgb: Scene-property synthesis with neural radiance fields,” in Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision , 2023, pp. 795–805
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