{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,23]],"date-time":"2026-08-23T10:52:35Z","timestamp":1787482355053,"version":"build-2736575974"},"reference-count":84,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,12,19]],"date-time":"2025-12-19T00:00:00Z","timestamp":1766102400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,12,19]],"date-time":"2025-12-19T00:00:00Z","timestamp":1766102400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100012165","name":"Key Technologies Research and Development Program","doi-asserted-by":"publisher","award":["2022ZD0160102"],"award-info":[{"award-number":["2022ZD0160102"]}],"id":[{"id":"10.13039\/501100012165","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62125603"],"award-info":[{"award-number":["62125603"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62206147"],"award-info":[{"award-number":["62206147"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62321005"],"award-info":[{"award-number":["62321005"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2336004"],"award-info":[{"award-number":["2336004"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int J Comput Vis"],"published-print":{"date-parts":[[2026,1]]},"DOI":"10.1007\/s11263-025-02602-4","type":"journal-article","created":{"date-parts":[[2025,12,19]],"date-time":"2025-12-19T13:49:40Z","timestamp":1766152180000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["OPONeRF: One-Point-One NeRF for Robust Few-shot Rendering"],"prefix":"10.1007","volume":"134","author":[{"given":"Yu","family":"Zheng","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yueqi","family":"Duan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kangfu","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongru","family":"Yan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiwen","family":"Lu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jie","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,12,19]]},"reference":[{"key":"2602_CR1","doi-asserted-by":"crossref","unstructured":"Barron, J.T., Mildenhall, B., Tancik, M., Hedman, P., Martin-Brualla, R. & Srinivasan, P.P. (2021). Mip-nerf: A multiscale representation for anti-aliasing neural radiance fields. In: ICCV, pp 5855\u20135864","DOI":"10.1109\/ICCV48922.2021.00580"},{"issue":"8","key":"2602_CR2","doi-asserted-by":"publisher","first-page":"1798","DOI":"10.1109\/TPAMI.2013.50","volume":"35","author":"Y Bengio","year":"2013","unstructured":"Bengio, Y., Courville, A., & Vincent, P. (2013). Representation learning: A review and new perspectives. T-PAMI, 35(8), 1798\u20131828.","journal-title":"T-PAMI"},{"key":"2602_CR3","doi-asserted-by":"crossref","unstructured":"Charatan, D., Li, S.L., Tagliasacchi, A. & Sitzmann, V. (2024). pixelsplat: 3d gaussian splats from image pairs for scalable generalizable 3d reconstruction. In: CVPR, pp 19457\u201319467","DOI":"10.1109\/CVPR52733.2024.01840"},{"key":"2602_CR4","doi-asserted-by":"crossref","unstructured":"Chen, A., Xu, Z., Zhao, F., Zhang, X., Xiang, F., Yu, J. & Su, H. (2021). Mvsnerf: Fast generalizable radiance field reconstruction from multi-view stereo. In: ICCV, pp 14124\u201314133","DOI":"10.1109\/ICCV48922.2021.01386"},{"key":"2602_CR5","doi-asserted-by":"crossref","unstructured":"Chen, S.E. & Williams, L. (1993). View interpolation for image synthesis. In: SIGGRAPH, pp 279\u2013288","DOI":"10.1145\/166117.166153"},{"key":"2602_CR6","doi-asserted-by":"crossref","unstructured":"Chen, Y. & Wang, X. (2022). Transformers as meta-learners for implicit neural representations. In: ECCV, pp 170\u2013187","DOI":"10.1007\/978-3-031-19790-1_11"},{"key":"2602_CR7","doi-asserted-by":"crossref","unstructured":"Chen, Y., Xu, H., Zheng, C., Zhuang, B., Pollefeys, M., Geiger, A., Cham, T.J. & Cai, J. (2024). Mvsplat: Efficient 3d gaussian splatting from sparse multi-view images. In: ECCV, pp 370\u2013386","DOI":"10.1007\/978-3-031-72664-4_21"},{"key":"2602_CR8","doi-asserted-by":"crossref","unstructured":"Debevec, P., Yu, Y. & Borshukov, G. (1998). Efficient view-dependent image-based rendering with projective texture-mapping. In: EGWR, pp 105\u2013116","DOI":"10.1007\/978-3-7091-6453-2_10"},{"key":"2602_CR9","doi-asserted-by":"crossref","unstructured":"Downs, L., Francis, A., Koenig, N., Kinman, B., Hickman, R., Reymann, K., McHugh, T.B. & Vanhoucke, V. (2022). Google scanned objects: A high-quality dataset of 3d scanned household items. In: ICRA, pp 2553\u20132560","DOI":"10.1109\/ICRA46639.2022.9811809"},{"key":"2602_CR10","unstructured":"Driess, D., Schubert, I., Florence, P., Li, Y. & Toussaint, M. (2022). Reinforcement learning with neural radiance fields. NeurIPS"},{"key":"2602_CR11","doi-asserted-by":"crossref","unstructured":"Du, H., Li, L., Liu, B. & Vasconcelos, N. (2020). Spot: Selective point cloud voting for better proposal in point cloud object detection. In: ECCV, pp 230\u2013247","DOI":"10.1007\/978-3-030-58621-8_14"},{"key":"2602_CR12","unstructured":"Fan, Z., Cong, W., Wen, K., Wang, K., Zhang, J., Ding, X., Xu, D., Ivanovic, B., Pavone, M. & Pavlakos, G. (2024). Instantsplat: Unbounded sparse-view pose-free gaussian splatting in 40 seconds. arXiv preprint arXiv:2403.20309 2(3):4"},{"issue":"2","key":"2602_CR13","first-page":"141","volume":"63","author":"A Fitzgibbon","year":"2005","unstructured":"Fitzgibbon, A., Wexler, Y., & Zisserman, A. (2005). Image-based rendering using image-based priors. IJCV, 63(2), 141\u2013151.","journal-title":"Image-based rendering using image-based priors. IJCV"},{"key":"2602_CR14","doi-asserted-by":"crossref","unstructured":"Flynn, J., Neulander, I., Philbin, J. & Snavely, N. (2016). Deepstereo: Learning to predict new views from the world\u2019s imagery. In: CVPR, pp 5515\u20135524","DOI":"10.1109\/CVPR.2016.595"},{"key":"2602_CR15","doi-asserted-by":"crossref","unstructured":"Flynn, J., Broxton, M., Debevec, P., DuVall, M., Fyffe, G., Overbeck, R., Snavely, N. & Tucker, R. (2019). Deepview: View synthesis with learned gradient descent. In: CVPR, pp 2367\u20132376","DOI":"10.1109\/CVPR.2019.00247"},{"key":"2602_CR16","doi-asserted-by":"crossref","unstructured":"Gao, C., Saraf, A., Kopf, J. & Huang, J.B. (2021). Dynamic view synthesis from dynamic monocular video. In: ICCV, pp 5712\u20135721","DOI":"10.1109\/ICCV48922.2021.00566"},{"key":"2602_CR17","unstructured":"Gao, K., Gao, Y., He. H., Lu, D., Xu, L. & Li, J. (2022). Nerf: Neural radiance field in 3d vision, a comprehensive review. arXiv preprint arXiv:2210.00379"},{"key":"2602_CR18","doi-asserted-by":"crossref","unstructured":"Greff, K., Belletti, F., Beyer, L., Doersch, C., Du, Y., Duckworth, D., Fleet, D,J., Gnanapragasam, D., Golemo, F., Herrmann, C. et al. (2022) Kubric: A scalable dataset generator. In: CVPR, pp 3749\u20133761","DOI":"10.1109\/CVPR52688.2022.00373"},{"key":"2602_CR19","volume-title":"Multiple view geometry in computer vision","author":"R Hartley","year":"2003","unstructured":"Hartley, R., & Zisserman, A. (2003). Multiple view geometry in computer vision. Cambridge University Press."},{"key":"2602_CR20","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S. & Sun, J. (2016). Deep residual learning for image recognition. In: CVPR, pp 770\u2013778","DOI":"10.1109\/CVPR.2016.90"},{"issue":"6","key":"2602_CR21","first-page":"1","volume":"35","author":"P Hedman","year":"2016","unstructured":"Hedman, P., Ritschel, T., Drettakis, G., & Brostow, G. (2016). Scalable inside-out image-based rendering. TOG, 35(6), 1\u201311.","journal-title":"Scalable inside-out image-based rendering. TOG"},{"key":"2602_CR22","doi-asserted-by":"crossref","unstructured":"Hore, A. & Ziou, D. (2010). Image quality metrics: Psnr vs. ssim. In: ICPR, pp 2366\u20132369","DOI":"10.1109\/ICPR.2010.579"},{"key":"2602_CR23","doi-asserted-by":"crossref","unstructured":"Hu, T., Liu, S., Chen, Y., Shen, T. & Jia, J. (2022). Efficientnerf: efficient neural radiance fields. In: CVPR, pp 12902\u201312911","DOI":"10.1109\/CVPR52688.2022.01256"},{"key":"2602_CR24","doi-asserted-by":"crossref","unstructured":"Huang, X., Zhang, Q., Feng, Y., Li, X., Wang, X. & Wang, Q. (2023). Local implicit ray function for generalizable radiance field representation. In: CVPR, pp 97\u2013107","DOI":"10.1109\/CVPR52729.2023.00018"},{"issue":"4","key":"2602_CR25","doi-asserted-by":"publisher","first-page":"1310","DOI":"10.1007\/s11263-023-01936-1","volume":"132","author":"N Jain","year":"2024","unstructured":"Jain, N., Kumar, S., & Van Gool, L. (2024). Learning robust multi-scale representation for neural radiance fields from unposed images. IJCV, 132(4), 1310\u20131335.","journal-title":"IJCV"},{"key":"2602_CR26","doi-asserted-by":"crossref","unstructured":"Jensen, R., Dahl, A., Vogiatzis, G., Tola, E. & Aan\u00e6s, H. (2014). Large scale multi-view stereopsis evaluation. In: CVPR, pp 406\u2013413","DOI":"10.1109\/CVPR.2014.59"},{"key":"2602_CR27","first-page":"26105","volume":"35","author":"Y Jeong","year":"2022","unstructured":"Jeong, Y., Shin, S., Lee, J., Choy, C., Anandkumar, A., Cho, M., & Park, J. (2022). Perfception: Perception using radiance fields. NeurIPS, 35, 26105\u201326121.","journal-title":"NeurIPS"},{"key":"2602_CR28","doi-asserted-by":"crossref","unstructured":"Johari, M.M., Lepoittevin, Y. & Fleuret, F. (2022). Geonerf: Generalizing nerf with geometry priors. In: CVPR, pp 18365\u201318375","DOI":"10.1109\/CVPR52688.2022.01782"},{"issue":"3","key":"2602_CR29","first-page":"165","volume":"18","author":"JT Kajiya","year":"1984","unstructured":"Kajiya, J. T., & Von Herzen, B. P. (1984). Ray tracing volume densities. SIGGRAPH, 18(3), 165\u2013174.","journal-title":"Ray tracing volume densities. SIGGRAPH"},{"issue":"4","key":"2602_CR30","doi-asserted-by":"publisher","first-page":"139","DOI":"10.1145\/3592433","volume":"42","author":"B Kerbl","year":"2023","unstructured":"Kerbl, B., Kopanas, G., Leimk\u00fchler, T., & Drettakis, G. (2023). 3d gaussian splatting for real-time radiance field rendering. TOG, 42(4), 139\u20131.","journal-title":"TOG"},{"key":"2602_CR31","unstructured":"Kosiorek, A.R., Strathmann, H., Zoran, D., Moreno, P., Schneider, R., Mokr\u00e1 S. & Rezende D.J. (2021). Nerf-vae: A geometry aware 3d scene generative model. In: ICML, pp 5742\u20135752"},{"key":"2602_CR32","doi-asserted-by":"crossref","unstructured":"Kurz, A., Neff, T., Lv, Z., Zollh\u00f6fer, M. & Steinberger, M. (2022). Adanerf: Adaptive sampling for real-time rendering of neural radiance fields. In: ECCV, pp 254\u2013270","DOI":"10.1007\/978-3-031-19790-1_16"},{"issue":"3","key":"2602_CR33","first-page":"611","volume":"132","author":"Y Lan","year":"2024","unstructured":"Lan, Y., Loy, C. C., & Dai, B. (2024). Correspondence distillation from nerf-based gan. IJCV, 132(3), 611\u2013631.","journal-title":"Correspondence distillation from nerf-based gan. IJCV"},{"key":"2602_CR34","doi-asserted-by":"crossref","unstructured":"Levoy, M. & Hanrahan, P. (1996). Light field rendering. In: SIGGRAPH, pp 31\u201342","DOI":"10.1145\/237170.237199"},{"key":"2602_CR35","doi-asserted-by":"crossref","unstructured":"Li, J., Feng, Z., She, Q., Ding, H., Wang, C. & Lee, G.H. (2021). Mine: Towards continuous depth mpi with nerf for novel view synthesis. In: ICCV, pp 12578\u201312588","DOI":"10.1109\/ICCV48922.2021.01235"},{"key":"2602_CR36","first-page":"13485","volume":"35","author":"L Li","year":"2022","unstructured":"Li, L., Shen, Z., Wang, Z., Shen, L., & Tan, P. (2022). Streaming radiance fields for 3d video synthesis. NeurIPS, 35, 13485\u201313498.","journal-title":"NeurIPS"},{"key":"2602_CR37","doi-asserted-by":"crossref","unstructured":"Li, T., Slavcheva, M., Zollhoefer, M., Green, S., Lassner, C., Kim, C., Schmidt, T., Lovegrove, S., Goesele, M., Newcombe, R. et al. (2022b) Neural 3d video synthesis from multi-view video. In: CVPR, pp 5521\u20135531","DOI":"10.1109\/CVPR52688.2022.00544"},{"key":"2602_CR38","doi-asserted-by":"crossref","unstructured":"Li, Y., Wang, N., Shi, J., Liu, J. & Hou, X. (2017). Revisiting batch normalization for practical domain adaptation. In: ICLR","DOI":"10.1016\/j.patcog.2018.03.005"},{"key":"2602_CR39","doi-asserted-by":"crossref","unstructured":"Liu, F., Zhang, C., Zheng, Y. & Duan, Y. (2023). Semantic ray: Learning a generalizable semantic field with cross-reprojection attention. In: CVPR, pp 17386\u201317396","DOI":"10.1109\/CVPR52729.2023.01668"},{"key":"2602_CR40","unstructured":"Liu, J., Xu, Z., Shi, R., Cheung, R.C. & So, H.K. (2020a). Dynamic sparse training: Find efficient sparse network from scratch with trainable masked layers. ICLR"},{"key":"2602_CR41","first-page":"15651","volume":"33","author":"L Liu","year":"2020","unstructured":"Liu, L., Gu, J., Zaw Lin, K., Chua, T. S., & Theobalt, C. (2020). Neural sparse voxel fields. NeurIPS, 33, 15651\u201315663.","journal-title":"Neural sparse voxel fields. NeurIPS"},{"key":"2602_CR42","doi-asserted-by":"crossref","unstructured":"Liu, S., Zhang, X., Zhang, Z., Zhang, R., Zhu, J.Y. & Russell, B. (2021). Editing conditional radiance fields. In: ICCV, pp 5773\u20135783","DOI":"10.1109\/ICCV48922.2021.00572"},{"key":"2602_CR43","doi-asserted-by":"crossref","unstructured":"Liu, Y., Peng, S., Liu, L., Wang, Q., Wang, P., Theobalt, C., Zhou, X. & Wang, W. (2022). Neural rays for occlusion-aware image-based rendering. In: CVPR, pp 7824\u20137833","DOI":"10.1109\/CVPR52688.2022.00767"},{"key":"2602_CR44","doi-asserted-by":"crossref","unstructured":"Lombardi, S., Simon, T., Saragih, J., Schwartz, G., Lehrmann, A. & Sheikh, Y. (2019). Neural volumes: Learning dynamic renderable volumes from images. TOG 38(4):65:1\u201365:14","DOI":"10.1145\/3306346.3323020"},{"key":"2602_CR45","doi-asserted-by":"crossref","unstructured":"Lu, Y., Ma, X., Yang, L., Zhang, T., Liu, Y., Chu, Q., Yan, J. & Ouyang, W. (2021). Geometry uncertainty projection network for monocular 3d object detection. In: ICCV, pp 3111\u20133121","DOI":"10.1109\/ICCV48922.2021.00310"},{"issue":"4","key":"2602_CR46","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3306346.3322980","volume":"38","author":"B Mildenhall","year":"2019","unstructured":"Mildenhall, B., Srinivasan, P. P., Ortiz-Cayon, R., Kalantari, N. K., Ramamoorthi, R., Ng, R., & Kar, A. (2019). Local light field fusion: Practical view synthesis with prescriptive sampling guidelines. TOG, 38(4), 1\u201314.","journal-title":"TOG"},{"key":"2602_CR47","doi-asserted-by":"crossref","unstructured":"Mildenhall, B., Srinivasan, P.P., Tancik, M., Barron, J.T., Ramamoorthi, R. & Ng, R. (2020). Nerf: Representing scenes as neural radiance fields for view synthesis. In: ECCV, pp 405\u2013421","DOI":"10.1007\/978-3-030-58452-8_24"},{"key":"2602_CR48","doi-asserted-by":"crossref","unstructured":"Mildenhall, B., Hedman, P., Martin-Brualla, R., Srinivasan, P.P. & Barron, J.T. (2022). Nerf in the dark: High dynamic range view synthesis from noisy raw images. In: CVPR, pp 16190\u201316199","DOI":"10.1109\/CVPR52688.2022.01571"},{"key":"2602_CR49","doi-asserted-by":"crossref","unstructured":"Niemeyer, M., Mescheder, L., Oechsle, M. & Geiger, A. (2020). Differentiable volumetric rendering: Learning implicit 3d representations without 3d supervision. In: CVPR, pp 3504\u20133515","DOI":"10.1109\/CVPR42600.2020.00356"},{"key":"2602_CR50","doi-asserted-by":"crossref","unstructured":"Pan, X., Lai, Z., Song, S. & Huang, G. (2022). Activenerf: Learning where to see with uncertainty estimation. In: ECCV, Springer, pp 230\u2013246","DOI":"10.1007\/978-3-031-19827-4_14"},{"key":"2602_CR51","doi-asserted-by":"crossref","unstructured":"Pumarola, A., Corona, E., Pons-Moll, G. & Moreno-Noguer, F. (2021). D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp 10318\u201310327","DOI":"10.1109\/CVPR46437.2021.01018"},{"key":"2602_CR52","doi-asserted-by":"crossref","unstructured":"Reiser, C., Peng, S., Liao, Y. & Geiger, A. (2021). Kilonerf: Speeding up neural radiance fields with thousands of tiny mlps. In: ICCV, pp 14335\u201314345","DOI":"10.1109\/ICCV48922.2021.01407"},{"key":"2602_CR53","doi-asserted-by":"crossref","unstructured":"Riegler G, Koltun V (2020) Free view synthesis. In: ECCV, pp 623\u2013640","DOI":"10.1007\/978-3-030-58529-7_37"},{"key":"2602_CR54","doi-asserted-by":"crossref","unstructured":"Shen, J., Ruiz, A., Agudo, A. & Moreno-Noguer, F. (2021). Stochastic neural radiance fields: Quantifying uncertainty in implicit 3d representations. In: 3DV, pp 972\u2013981","DOI":"10.1109\/3DV53792.2021.00105"},{"key":"2602_CR55","doi-asserted-by":"crossref","unstructured":"Sitzmann, V., Thies, J., Heide, F., Nie\u00dfner, M., Wetzstein, G. & Zollhofer, M. (2019a). Deepvoxels: Learning persistent 3d feature embeddings. In: CVPR, pp 2437\u20132446","DOI":"10.1109\/CVPR.2019.00254"},{"key":"2602_CR56","first-page":"1121","volume":"32","author":"V Sitzmann","year":"2019","unstructured":"Sitzmann, V., Zollh\u00f6fer, M., & Wetzstein, G. (2019). Scene representation networks: Continuous 3d-structure-aware neural scene representations. NeurIPS, 32, 1121\u20131132.","journal-title":"NeurIPS"},{"key":"2602_CR57","doi-asserted-by":"crossref","unstructured":"Song, S. & Funkhouser, T. (2019). Neural illumination: Lighting prediction for indoor environments. In: CVPR, pp 6918\u20136926","DOI":"10.1109\/CVPR.2019.00708"},{"issue":"1","key":"2602_CR58","first-page":"1929","volume":"15","author":"N Srivastava","year":"2014","unstructured":"Srivastava, N., Hinton, G., Krizhevsky, A., Sutskever, I., & Salakhutdinov, R. (2014). Dropout: a simple way to prevent neural networks from overfitting. JMLR, 15(1), 1929\u20131958.","journal-title":"JMLR"},{"key":"2602_CR59","doi-asserted-by":"crossref","unstructured":"Suhail, M., Esteves, C., Sigal, L. & Makadia, A. (2022). Generalizable patch-based neural rendering. In: ECCV, pp 156\u2013174","DOI":"10.1007\/978-3-031-19824-3_10"},{"key":"2602_CR60","first-page":"7537","volume":"33","author":"M Tancik","year":"2020","unstructured":"Tancik, M., Srinivasan, P., Mildenhall, B., Fridovich-Keil, S., Raghavan, N., Singhal, U., Ramamoorthi, R., Barron, J., & Ng, R. (2020). Fourier features let networks learn high frequency functions in low dimensional domains. NeurIPS, 33, 7537\u20137547.","journal-title":"NeurIPS"},{"key":"2602_CR61","doi-asserted-by":"crossref","unstructured":"Tancik, M., Casser, V., Yan, X., Pradhan, S., Mildenhall, B., Srinivasan, P.P., Barron, J.T. & Kretzschmar, H. (2022). Block-nerf: Scalable large scene neural view synthesis. In: CVPR, pp 8248\u20138258","DOI":"10.1109\/CVPR52688.2022.00807"},{"key":"2602_CR62","doi-asserted-by":"crossref","unstructured":"Tian, F., Du, S. & Duan, Y. (2023). Mononerf: Learning a generalizable dynamic radiance field from monocular videos. In: ICCV","DOI":"10.1109\/ICCV51070.2023.01641"},{"key":"2602_CR63","doi-asserted-by":"crossref","unstructured":"Trevithick, A. & Yang, B. (2021). GRF: Learning a general radiance field for 3d representation and rendering. In: CVPR, pp 15182\u201315192","DOI":"10.1109\/ICCV48922.2021.01490"},{"key":"2602_CR64","doi-asserted-by":"crossref","unstructured":"Turki, H., Ramanan, D. & Satyanarayanan, M. (2022). Mega-nerf: Scalable construction of large-scale nerfs for virtual fly-throughs. In: CVPR, pp 12922\u201312931","DOI":"10.1109\/CVPR52688.2022.01258"},{"key":"2602_CR65","doi-asserted-by":"crossref","unstructured":"Wang, C., Wang, A., Li, J., Yuille, A. & Xie, C. (2024). Benchmarking robustness in neural radiance fields. In: CVPRW","DOI":"10.1109\/CVPRW63382.2024.00298"},{"key":"2602_CR66","unstructured":"Wang, P., Chen, X., Chen, T., Venugopalan, S., Wang, Z. et al. (2023) Is attention all nerf needs? In: ICLR"},{"key":"2602_CR67","doi-asserted-by":"crossref","unstructured":"Wang, Q., Wang, Z., Genova, K., Srinivasan, P.P., Zhou, H., Barron, J.T., Martin-Brualla, R., Snavely, N. & Funkhouser, T. (2021). Ibrnet: Learning multi-view image-based rendering. In: CVPR, pp 4690\u20134699","DOI":"10.1109\/CVPR46437.2021.00466"},{"key":"2602_CR68","doi-asserted-by":"crossref","unstructured":"Wei, Y., Liu, S., Rao, Y., Zhao, W., Lu, J. & Zhou, J. (2021). Nerfingmvs: Guided optimization of neural radiance fields for indoor multi-view stereo. In: ICCV, pp 5610\u20135619","DOI":"10.1109\/ICCV48922.2021.00556"},{"key":"2602_CR69","first-page":"1120","volume":"2","author":"OJ Woodford","year":"2007","unstructured":"Woodford, O. J., Reid, I. D., Torr, P. H., & Fitzgibbon, A. W. (2007). On new view synthesis using multiview stereo. BMVC, 2, 1120\u20131129.","journal-title":"BMVC"},{"key":"2602_CR70","doi-asserted-by":"crossref","unstructured":"Wu, G., Yi, T., Fang, J., Xie, L., Zhang, X., Wei, W., Liu, W., Tian, Q. & Xinggang, W. (2024). 4d gaussian splatting for real-time dynamic scene rendering. In: CVPR","DOI":"10.1109\/CVPR52733.2024.01920"},{"key":"2602_CR71","doi-asserted-by":"crossref","unstructured":"Xu, C., Wu, B., Hou, J., Tsai, S., Li, R., Wang, J., Zhan, W., He, Z., Vajda, P., Keutzer, K. et al. (2023) Nerf-det: Learning geometry-aware volumetric representation for multi-view 3d object detection. In: ICCV","DOI":"10.1109\/ICCV51070.2023.02131"},{"key":"2602_CR72","doi-asserted-by":"crossref","unstructured":"Xu, Q., Xu, Z., Philip, J., Bi, S., Shu, Z., Sunkavalli, K. & Neumann, U. (2022). Point-nerf: Point-based neural radiance fields. In: CVPR, pp 5438\u20135448","DOI":"10.1109\/CVPR52688.2022.00536"},{"key":"2602_CR73","doi-asserted-by":"crossref","unstructured":"Yang, S., Wang, Y., Van De\u00a0Weijer, J., Herranz, L. & Jui, S. (2021). Generalized source-free domain adaptation. In: ICCV, pp 8978\u20138987","DOI":"10.1109\/ICCV48922.2021.00885"},{"key":"2602_CR74","doi-asserted-by":"crossref","unstructured":"Yang, Y., Hayat, M., Jin, Z., Ren, C. & Lei, Y. (2023). Geometry and uncertainty-aware 3d point cloud class-incremental semantic segmentation. In: CVPR, pp 21759\u201321768","DOI":"10.1109\/CVPR52729.2023.02084"},{"key":"2602_CR75","doi-asserted-by":"crossref","unstructured":"Yao, Y., Luo, Z., Li, S., Fang, T. & Quan, L. (2018). Mvsnet: Depth inference for unstructured multi-view stereo. In: ECCV, pp 767\u2013783","DOI":"10.1007\/978-3-030-01237-3_47"},{"key":"2602_CR76","doi-asserted-by":"crossref","unstructured":"Yen-Chen, L., Florence, P., Barron, J.T., Rodriguez, A., Isola, P. & Lin, T.Y. (2021). inerf: Inverting neural radiance fields for pose estimation. In: IROS, pp 1323\u20131330","DOI":"10.1109\/IROS51168.2021.9636708"},{"key":"2602_CR77","doi-asserted-by":"crossref","unstructured":"Yu, A., Ye, V., Tancik, M. & Kanazawa, A. (2021). pixelnerf: Neural radiance fields from one or few images. In: CVPR, pp 4578\u20134587","DOI":"10.1109\/CVPR46437.2021.00455"},{"key":"2602_CR78","doi-asserted-by":"crossref","unstructured":"Yuan, Y.J., Sun, Y.T., Lai, Y.K., Ma, Y., Jia, R. & Gao, L. (2022). Nerf-editing: geometry editing of neural radiance fields. In: CVPR, pp 18353\u201318364","DOI":"10.1109\/CVPR52688.2022.01781"},{"key":"2602_CR79","doi-asserted-by":"crossref","unstructured":"Zhang, R., Isola, P., Efros, A.A., Shechtman, E. & Wang, O. (2018). The unreasonable effectiveness of deep features as a perceptual metric. In: CVPR, pp 586\u2013595","DOI":"10.1109\/CVPR.2018.00068"},{"key":"2602_CR80","doi-asserted-by":"crossref","unstructured":"Zheng, Y., Duan, Y., Lu, J., Zhou, J. & Tian, Q. (2022). Hyperdet3d: Learning a scene-conditioned 3d object detector. In: CVPR, pp 5585\u20135594","DOI":"10.1109\/CVPR52688.2022.00550"},{"key":"2602_CR81","doi-asserted-by":"crossref","unstructured":"Zhi, S., Laidlow, T., Leutenegger, S. & Davison, A.J. (2021). In-place scene labelling and understanding with implicit scene representation. In: ICCV, pp 15838\u201315847","DOI":"10.1109\/ICCV48922.2021.01554"},{"key":"2602_CR82","doi-asserted-by":"crossref","unstructured":"Zhou, T., Tucker, R., Flynn, J., Fyffe, G. & Snavely, N. (2018). Stereo magnification: Learning view synthesis using multiplane images. TOG 37(4)","DOI":"10.1145\/3197517.3201323"},{"issue":"8","key":"2602_CR83","doi-asserted-by":"publisher","first-page":"2032","DOI":"10.1007\/s11263-023-01803-z","volume":"131","author":"Y Zhou","year":"2023","unstructured":"Zhou, Y., Wu, H., Liu, W., Xiong, Z., Qin, J., & He, S. (2023). Single-view view synthesis with self-rectified pseudo-stereo. IJCV, 131(8), 2032\u20132043.","journal-title":"IJCV"},{"issue":"10","key":"2602_CR84","doi-asserted-by":"publisher","first-page":"2649","DOI":"10.1007\/s11263-023-01829-3","volume":"131","author":"J Zhu","year":"2023","unstructured":"Zhu, J., Zhu, H., Zhang, Q., Zhu, F., Ma, Z., & Cao, X. (2023). Pyramid nerf: Frequency guided fast radiance field optimization. IJCV, 131(10), 2649\u20132664.","journal-title":"IJCV"}],"container-title":["International Journal of Computer Vision"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11263-025-02602-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11263-025-02602-4","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11263-025-02602-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,20]],"date-time":"2026-02-20T15:39:15Z","timestamp":1771601955000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11263-025-02602-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,19]]},"references-count":84,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2026,1]]}},"alternative-id":["2602"],"URL":"https:\/\/doi.org\/10.1007\/s11263-025-02602-4","relation":{},"ISSN":["0920-5691","1573-1405"],"issn-type":[{"value":"0920-5691","type":"print"},{"value":"1573-1405","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,12,19]]},"assertion":[{"value":"22 July 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 November 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 December 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflicts of Interest"}},{"value":"This article does not contain any studies with human participants or animals.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical Approval"}}],"article-number":"3"}}