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NeRF in the Wild: Neural Radiance Fields for Unconstrained Photo Collections, , , , , и . (2020)cite arxiv:2008.02268Comment: Project website: https://nerf-w.github.io. Ricardo Martin-Brualla, Noha Radwan, and Mehdi S. M. Sajjadi contributed equally to this work. Updated with results for three additional scenes.Kubric: A scalable dataset generator., , , , , , , , , и 24 other автор(ы). CoRR, (2022)NeRF in the Wild: Neural Radiance Fields for Unconstrained Photo Collections., , , , , и . CVPR, стр. 7210-7219. Computer Vision Foundation / IEEE, (2021)RegNeRF: Regularizing Neural Radiance Fields for View Synthesis from Sparse Inputs., , , , , и . CVPR, стр. 5470-5480. IEEE, (2022)NeSF: Neural Semantic Fields for Generalizable Semantic Segmentation of 3D Scenes., , , , , , , , и . Trans. Mach. Learn. Res., (2022)Perspectives on Deep Multimodel Robot Learning., , , , , , , , и . ISRR, том 10 из Springer Proceedings in Advanced Robotics, стр. 17-24. Springer, (2017)Kubric: A scalable dataset generator., , , , , , , , , и 24 other автор(ы). CVPR, стр. 3739-3751. IEEE, (2022)Scene Representation Transformer: Geometry-Free Novel View Synthesis Through Set-Latent Scene Representations., , , , , , , , , и 3 other автор(ы). CVPR, стр. 6219-6228. IEEE, (2022)Multimodal interaction-aware motion prediction for autonomous street crossing., , и . Int. J. Robotics Res., (2020)Leveraging sparse and dense features for reliable state estimation in urban environments.. University of Freiburg, Freiburg im Breisgau, Germany, (2019)