{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T06:00:29Z","timestamp":1743055229042,"version":"3.40.3"},"publisher-location":"Cham","reference-count":25,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031750090"},{"type":"electronic","value":"9783031750106"}],"license":[{"start":{"date-parts":[[2024,11,20]],"date-time":"2024-11-20T00:00:00Z","timestamp":1732060800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,11,20]],"date-time":"2024-11-20T00:00:00Z","timestamp":1732060800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-3-031-75010-6_3","type":"book-chapter","created":{"date-parts":[[2024,11,19]],"date-time":"2024-11-19T01:37:47Z","timestamp":1731980267000},"page":"22-31","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Novel Positional Encoding Methods for\u00a0Neural Rendering"],"prefix":"10.1007","author":[{"given":"Daniel","family":"Molina-Pinel","sequence":"first","affiliation":[]},{"given":"Jorge","family":"Garc\u00eda-Gonz\u00e1lez","sequence":"additional","affiliation":[]},{"given":"Enrique","family":"Dom\u00ednguez","sequence":"additional","affiliation":[]},{"given":"Ezequiel","family":"L\u00f3pez-Rubio","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,11,20]]},"reference":[{"key":"3_CR1","doi-asserted-by":"publisher","unstructured":"Barron, J.T., Mildenhall, B., Verbin, D., Srinivasan, P.P., Hedman, P.: Mip-nerf 360: unbounded anti-aliased neural radiance fields. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5460\u20135469. IEEE (2022). https:\/\/doi.org\/10.1109\/CVPR52688.2022.00539","DOI":"10.1109\/CVPR52688.2022.00539"},{"key":"3_CR2","doi-asserted-by":"publisher","unstructured":"Boss, M., Braun, R., Jampani, V., Barron, J.T., Liu, C., Lensch, H.P.: Nerd: neural reflectance decomposition from image collections. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 12,664\u201312,674. IEEE (2021). https:\/\/doi.org\/10.1109\/ICCV48922.2021.01245","DOI":"10.1109\/ICCV48922.2021.01245"},{"key":"3_CR3","first-page":"10691","volume":"34","author":"M Boss","year":"2021","unstructured":"Boss, M., Jampani, V., Braun, R., Liu, C., Barron, J., Lensch, H.: Neural-pil: neural pre-integrated lighting for reflectance decomposition. Adv. Neural. Inf. Process. Syst. 34, 10691\u201310704 (2021)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"3_CR4","doi-asserted-by":"publisher","unstructured":"Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: tensorial radiance fields. In: European Conference on Computer Vision. In: European Conference on Computer Vision, pp. 333\u2013350. Springer (2022). https:\/\/doi.org\/10.1007\/978-3-031-19824-3_20","DOI":"10.1007\/978-3-031-19824-3_20"},{"key":"3_CR5","doi-asserted-by":"crossref","unstructured":"Franke, L., R\u00fcckert, D., Fink, L., Stamminger, M.: Trips: Trilinear point splatting for real-time radiance field rendering. ArXiv abs\/2401.06003 (2024). https:\/\/api.semanticscholar.org\/CorpusID:266933604","DOI":"10.1111\/cgf.15012"},{"key":"3_CR6","doi-asserted-by":"publisher","unstructured":"Gao, C., Saraf, A., Kopf, J., Huang, J.B.: Dynamic view synthesis from dynamic monocular video. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 5692\u20135701. IEEE (2021). https:\/\/doi.org\/10.1109\/ICCV48922.2021.00566","DOI":"10.1109\/ICCV48922.2021.00566"},{"key":"3_CR7","unstructured":"Gardner, J.A.D., Kashin, E., Egger, B., Smith, W.A.P.: The sky\u2019s the limit: Re-lightable outdoor scenes via a sky-pixel constrained illumination prior and outside-in visibility. ArXiv abs\/2311.16937 (2023). https:\/\/api.semanticscholar.org\/CorpusID:265725234"},{"key":"3_CR8","doi-asserted-by":"crossref","unstructured":"Kerbl, B., Kopanas, G., Leimk\u00fchler, T., Drettakis, G.: 3d gaussian splatting for real-time radiance field rendering. ACM Trans. Graph. 42(4) (2023). https:\/\/repo-sam.inria.fr\/fungraph\/3d-gaussian-splatting\/","DOI":"10.1145\/3592433"},{"key":"3_CR9","doi-asserted-by":"crossref","unstructured":"Krizhevsky, A., Sutskever, I., Hinton, G.E.: Imagenet classification with deep convolutional neural networks. Commun. ACM 60, 84 \u2013 90 (2012). https:\/\/api.semanticscholar.org\/CorpusID:195908774","DOI":"10.1145\/3065386"},{"key":"3_CR10","doi-asserted-by":"crossref","unstructured":"Li, T., et al.: Neural 3D video synthesis from multi-view video. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 5521\u20135531 (2022)","DOI":"10.1109\/CVPR52688.2022.00544"},{"key":"3_CR11","doi-asserted-by":"crossref","unstructured":"Martin-Brualla, R., Radwan, N., Sajjadi, M.S., Barron, J.T., Dosovitskiy, A., Duckworth, D.: Nerf in the wild: neural radiance fields for unconstrained photo collections. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 7210\u20137219 (2021)","DOI":"10.1109\/CVPR46437.2021.00713"},{"key":"3_CR12","doi-asserted-by":"crossref","unstructured":"Mildenhall, B., Srinivasan, P.P., Tancik, M., Barron, J.T., Ramamoorthi, R., Ng, R.: Nerf: representing scenes as neural radiance fields for view synthesis. In: ECCV (2020)","DOI":"10.1007\/978-3-030-58452-8_24"},{"key":"3_CR13","doi-asserted-by":"publisher","unstructured":"M\u00fcller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Trans. Graph. 41, 1\u201315 (2022). https:\/\/doi.org\/10.1145\/3528223.3530127","DOI":"10.1145\/3528223.3530127"},{"key":"3_CR14","doi-asserted-by":"publisher","unstructured":"Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: neural radiance fields for dynamic scenes. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 10,313\u201310,322. IEEE (2021). https:\/\/doi.org\/10.1109\/CVPR46437.2021.01018","DOI":"10.1109\/CVPR46437.2021.01018"},{"key":"3_CR15","unstructured":"Rahaman, N., Baratin, A., Arpit, D., Dr\u00e4xler, F., Lin, M., Hamprecht, F., Bengio, Y., Courville, A.C.: On the spectral bias of neural networks (2018)"},{"key":"3_CR16","doi-asserted-by":"crossref","unstructured":"Song, L., et al.: Nerfplayer: a streamable dynamic scene representation with decomposed neural radiance fields. IEEE Trans. Visual Comput. Graphics 29(5), 2732\u20132742 (2023)","DOI":"10.1109\/TVCG.2023.3247082"},{"key":"3_CR17","doi-asserted-by":"publisher","unstructured":"Srinivasan, P.P., Deng, B., Zhang, X., Tancik, M., Mildenhall, B., Barron, J.T.: Nerv: neural reflectance and visibility fields for relighting and view synthesis. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 7491\u20137500. IEEE (2021). https:\/\/doi.org\/10.1109\/CVPR46437.2021.00741","DOI":"10.1109\/CVPR46437.2021.00741"},{"key":"3_CR18","unstructured":"Tancik, M., et al.: Fourier features let networks learn high frequency functions in low dimensional domains. Adv. Neural. Inf. Process. Syst. 33, 7537\u20137547 (2020)"},{"key":"3_CR19","doi-asserted-by":"crossref","unstructured":"Tancik, M., et\u00a0al.: Nerfstudio: a modular framework for neural radiance field development. In: ACM SIGGRAPH 2023 Conference Proceedings, pp. 1\u201312 (2023)","DOI":"10.1145\/3588432.3591516"},{"key":"3_CR20","unstructured":"Vaswani, A., et al.: Attention is all you need. Adv. Neural Inf. Proce. Syst. (2017)"},{"key":"3_CR21","doi-asserted-by":"crossref","unstructured":"Wang, F., Tan, S., Li, X., Tian, Z., Liu, H.: Mixed neural voxels for fast multi-view video synthesis. arXiv preprint arXiv:2212.00190 (2022)","DOI":"10.1109\/ICCV51070.2023.01805"},{"key":"3_CR22","doi-asserted-by":"crossref","unstructured":"Yariv, L., .: Bakedsdf: Meshing neural sdfs for real-time view synthesis. arXiv preprint arXiv:2302.14859 (2023)","DOI":"10.1145\/3588432.3591536"},{"key":"3_CR23","doi-asserted-by":"publisher","unstructured":"Zhang, K., Luan, F., Wang, Q., Bala, K., Snavely, N.: Physg: inverse rendering with spherical gaussians for physics-based material editing and relighting. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5449\u20135458. IEEE (2021). https:\/\/doi.org\/10.1109\/CVPR46437.2021.00541","DOI":"10.1109\/CVPR46437.2021.00541"},{"key":"3_CR24","doi-asserted-by":"crossref","unstructured":"Zhang, R., Isola, P., Efros, A.A., Shechtman, E., Wang, O.: The unreasonable effectiveness of deep features as a perceptual metric. In: CVPR (2018)","DOI":"10.1109\/CVPR.2018.00068"},{"issue":"6","key":"3_CR25","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3478513.3480500","volume":"40","author":"X Zhang","year":"2021","unstructured":"Zhang, X., Srinivasan, P.P., Deng, B., Debevec, P., Freeman, W.T., Barron, J.T.: Nerfactor: neural factorization of shape and reflectance under an unknown illumination. ACM Trans. Graph. (TOG) 40(6), 1\u201318 (2021)","journal-title":"ACM Trans. Graph. (TOG)"}],"container-title":["Lecture Notes in Networks and Systems","The 19th International Conference on Soft Computing Models in Industrial and Environmental Applications SOCO 2024"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-75010-6_3","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,19]],"date-time":"2024-11-19T02:02:59Z","timestamp":1731981779000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-75010-6_3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,20]]},"ISBN":["9783031750090","9783031750106"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-75010-6_3","relation":{},"ISSN":["2367-3370","2367-3389"],"issn-type":[{"type":"print","value":"2367-3370"},{"type":"electronic","value":"2367-3389"}],"subject":[],"published":{"date-parts":[[2024,11,20]]},"assertion":[{"value":"20 November 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"SOCO","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Soft Computing Models in Industrial and Environmental Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Salamanca","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Spain","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 October 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 October 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icscmiea2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/2024.sococonference.eu\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}