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In this paper, we introduce a new challenge for synthesizing novel view images in practical environments with limited input multi-view images and varying lighting conditions.
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Local light field fusion: Practical view synthesis with prescriptive sampling guidelines
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Liu, Y.; Li, Y.; You, S.; and Lu, F. 2020 · 2020
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Nerf: Representing scenes as neural radiance fields for view synthesis
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Nerf_pl : a pytorch-lightning implementation of NeRF
Quei-An, C. 2020 · 2020
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Mvsnerf: Fast generalizable radiance field reconstruction from multi-view stereo
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Stereo radiance fields (srf): Learning view synthesis for sparse views of novel scenes
Chibane, J.; Bansal, A.; Lazova, V.; and Pons-Moll, G. 2021 · 2021
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Jain, A.; Tancik, M.; and Abbeel, P. 2021 · 2021
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Openrooms: An open framework for photorealistic indoor scene datasets
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Nerf in the wild: Neural radiance fields for unconstrained photo collections
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NeROIC: neural rendering of objects from online image collections
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Regnerf: Regularizing neural radiance fields for view synthesis from sparse inputs
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Dreamfusion: Text-to-3d using 2d diffusion
Poole, B.; Jain, A.; Barron, J. T.; and Mildenhall, B. 2022 · 2022
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Dense depth priors for neural radiance fields from sparse input views
Roessle, B.; Barron, J. T.; Mildenhall, B.; Srinivasan, P. P.; and Nießner, M. 2022 · 2022
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Nerf for outdoor scene relighting
Rudnev, V.; Elgharib, M.; Smith, W.; Liu, L.; Golyanik, V.; and Theobalt, C. 2022 · 2022
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Ibrnet: Learning multi-view image-based rendering
Wang, Q.; Wang, Z.; Genova, K.; Srinivasan, P. P.; Zhou, H.; Barron, J. T.; Martin-Brualla, R.; Snavely, N.; and Funkhouser, T. 2021 · 2021
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pixelnerf: Neural radiance fields from one or few images
Yu, A.; Ye, V.; Tancik, M.; and Kanazawa, A. 2021 · 2021
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SAMURAI: Shape And Material from Unconstrained Real-world Arbitrary Image collections
Boss, M.; Engelhardt, A.; Kar, A.; Li, Y.; Sun, D.; Barron, J. T.; Lensch, H. P.; and Jampani, V. 2022 · 2022
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Hallucinated Neural Radiance Fields in the Wild
Chen, X.; Zhang, Q.; Li, X.; Chen, Y.; Feng, Y.; Wang, X.; and Wang, J. 2022 · 2022
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PIE-Net: Photometric Invariant Edge Guided Network for Intrinsic Image Decomposition
Das, P.; Karaoglu, S.; and Gevers, T. 2022 · 2022
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Depth-supervised nerf: Fewer views and faster training for free
Deng, K.; Liu, A.; Zhu, J.-Y.; and Ramanan, D. 2022 · 2022
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CLIP-NeRF: Text-and-Image Driven Manipulation of Neural Radiance Fields
Wang, C.; Chai, M.; He, M.; Chen, D.; and Liao, J. 2022 · 2022
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Novel view synthesis with diffusion models
Watson, D.; Chan, W.; Martin-Brualla, R.; Ho, J.; Tagliasacchi, A.; and Norouzi, M. 2022 · 2022
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SinNeRF: Training Neural Radiance Fields on Complex Scenes from a Single Image
Xu, D.; Jiang, Y.; Wang, P.; Fan, Z.; Shi, H.; and Wang, Z. 2022 · 2022
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IntrinsicNeRF: Learning Intrinsic Neural Radiance Fields for Editable Novel View Synthesis
Ye, W.; Chen, S.; Bao, C.; Bao, H.; Pollefeys, M.; Cui, Z.; and Zhang, G. 2022 · 2022
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MAIR: Multi-view Attention Inverse Rendering with 3D Spatially-Varying Lighting Estimation
Choi, J.; Lee, S.; Park, H.; Jung, S.-W.; Kim, I.-J.; and Cho, J. 2023 · 2023
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Nerdi: Single-view nerf synthesis with language-guided diffusion as general image priors
Deng, C.; Jiang, C.; Qi, C. R.; Yan, X.; Zhou, Y.; Guibas, L.; Anguelov, D.; et al. 2023 · 2023
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Palettenerf: Palette-based appearance editing of neural radiance fields
Kuang, Z.; Luan, F.; Bi, S.; Shu, Z.; Wetzstein, G.; and Sunkavalli, K. 2023 · 2023
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ReLight My NeRF: A Dataset for Novel View Synthesis and Relighting of Real World Objects
Toschi, M.; De Matteo, R.; Spezialetti, R.; De Gregorio, D.; Di Stefano, L.; and Salti, S. 2023 · 2023
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Wynn, J.; and Turmukhambetov, D. 2023 · 2023
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FreeNeRF: Improving Few-shot Neural Rendering with Free Frequency Regularization
Yang, J.; Pavone, M.; and Wang, Y. 2023 · 2023
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Complementary Intrinsics From Neural Radiance Fields and CNNs for Outdoor Scene Relighting
Yang, S.; Cui, X.; Zhu, Y.; Tang, J.; Li, S.; Yu, Z.; and Shi, B. 2023 · 2023
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