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In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. pp. 13\u201323.","DOI":"10.1109\/CVPR52729.2023.00010"},{"key":"10.1016\/j.cviu.2026.104714_b65","series-title":"Computer Vision\u2013ECCV 2020: 16th European Conference, Glasgow, UK, August 23\u201328, 2020, Proceedings, Part IV 16","first-page":"544","article-title":"Learning to factorize and relight a city","author":"Liu","year":"2020"},{"key":"10.1016\/j.cviu.2026.104714_b66","first-page":"15651","article-title":"Neural sparse voxel fields","volume":"33","author":"Liu","year":"2020","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.cviu.2026.104714_b67","doi-asserted-by":"crossref","unstructured":"Liu,\u00a0C., Kumar,\u00a0S., Gu,\u00a0S., Timofte,\u00a0R., Van\u00a0Gool,\u00a0L., 2023. Single image depth prediction made better: A multivariate gaussian take. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. pp. 17346\u201317356.","DOI":"10.1109\/CVPR52729.2023.01664"},{"issue":"4","key":"10.1016\/j.cviu.2026.104714_b68","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3306346.3323020","article-title":"Neural volumes: learning dynamic renderable volumes from images","volume":"38","author":"Lombardi","year":"2019","journal-title":"ACM Trans. Graph."},{"issue":"4","key":"10.1016\/j.cviu.2026.104714_b69","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3450626.3459863","article-title":"Mixture of volumetric primitives for efficient neural rendering","volume":"40","author":"Lombardi","year":"2021","journal-title":"ACM Trans. Graph. 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In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. pp. 76\u201387.","DOI":"10.1109\/CVPR52729.2023.00016"},{"key":"10.1016\/j.cviu.2026.104714_b95","series-title":"European Conference on Computer Vision","first-page":"612","article-title":"R2l: Distilling neural radiance field to neural light field for efficient novel view synthesis","author":"Wang","year":"2022"},{"key":"10.1016\/j.cviu.2026.104714_b96","doi-asserted-by":"crossref","unstructured":"Wang,\u00a0F., Tan,\u00a0S., Li,\u00a0X., Tian,\u00a0Z., Song,\u00a0Y., Liu,\u00a0H., 2023. Mixed Neural Voxels for Fast Multi-view Video Synthesis. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision. 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In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. pp. 4389\u20134398.","DOI":"10.1109\/CVPR52733.2024.00420"},{"key":"10.1016\/j.cviu.2026.104714_b104","doi-asserted-by":"crossref","unstructured":"Xu,\u00a0Z., Peng,\u00a0S., Lin,\u00a0H., He,\u00a0G., Sun,\u00a0J., Shen,\u00a0Y., Bao,\u00a0H., Zhou,\u00a0X., 2024. 4k4d: Real-time 4d view synthesis at 4k resolution. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. pp. 20029\u201320040.","DOI":"10.1109\/CVPR52733.2024.01893"},{"key":"10.1016\/j.cviu.2026.104714_b105","doi-asserted-by":"crossref","unstructured":"Xu,\u00a0Q., Xu,\u00a0Z., Philip,\u00a0J., Bi,\u00a0S., Shu,\u00a0Z., Sunkavalli,\u00a0K., Neumann,\u00a0U., 2022. Point-nerf: Point-based neural radiance fields. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. pp. 5438\u20135448.","DOI":"10.1109\/CVPR52688.2022.00536"},{"key":"10.1016\/j.cviu.2026.104714_b106","doi-asserted-by":"crossref","unstructured":"Yang,\u00a0Z., Gao,\u00a0X., Zhou,\u00a0W., Jiao,\u00a0S., Zhang,\u00a0Y., Jin,\u00a0X., 2024a. Deformable 3d gaussians for high-fidelity monocular dynamic scene reconstruction. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. pp. 20331\u201320341.","DOI":"10.1109\/CVPR52733.2024.01922"},{"key":"10.1016\/j.cviu.2026.104714_b107","unstructured":"Yang,\u00a0Z., Yang,\u00a0H., Pan,\u00a0Z., Zhang,\u00a0L., 2024b. Real-time Photorealistic Dynamic Scene Representation and Rendering with 4D Gaussian Splatting. In: International Conference on Learning Representations. ICLR."},{"key":"10.1016\/j.cviu.2026.104714_b108","unstructured":"Yao,\u00a0Y., Zeng,\u00a0Z., Gu,\u00a0C., Zhu,\u00a0X., Zhang,\u00a0L., 2025. Reflective Gaussian Splatting. In: The Thirteenth International Conference on Learning Representations. ICLR."},{"key":"10.1016\/j.cviu.2026.104714_b109","doi-asserted-by":"crossref","unstructured":"Yu,\u00a0A., Li,\u00a0R., Tancik,\u00a0M., Li,\u00a0H., Ng,\u00a0R., Kanazawa,\u00a0A., 2021. Plenoctrees for real-time rendering of neural radiance fields. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision. pp. 5752\u20135761.","DOI":"10.1109\/ICCV48922.2021.00570"},{"key":"10.1016\/j.cviu.2026.104714_b110","doi-asserted-by":"crossref","unstructured":"Zhang,\u00a0R., Isola,\u00a0P., Efros,\u00a0A.A., Shechtman,\u00a0E., Wang,\u00a0O., 2018. The unreasonable effectiveness of deep features as a perceptual metric. 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