{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,14]],"date-time":"2026-09-14T09:04:43Z","timestamp":1789376683310,"version":"build-2803163510"},"publisher-location":"Cham","reference-count":49,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032373823","type":"print"},{"value":"9783032373830","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"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":[[2026]]},"DOI":"10.1007\/978-3-032-37383-0_19","type":"book-chapter","created":{"date-parts":[[2026,9,14]],"date-time":"2026-09-14T08:28:22Z","timestamp":1789374502000},"page":"318-335","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["FLEG: Feed-Forward Language Embedded Gaussian Splatting from\u00a0Any Views via\u00a0Compact Semantic Representation"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7218-4978","authenticated-orcid":false,"given":"Qijian","family":"Tian","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-3051-7285","authenticated-orcid":false,"given":"Jiayu","family":"Ying","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0944-8667","authenticated-orcid":false,"given":"Xuhong","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6945-7437","authenticated-orcid":false,"given":"Yuan","family":"Xie","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1653-4341","authenticated-orcid":false,"given":"Lizhuang","family":"Ma","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9346-1196","authenticated-orcid":false,"given":"Xin","family":"Tan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,9,15]]},"reference":[{"key":"19_CR1","doi-asserted-by":"crossref","unstructured":"Anderson, P., et al.: Vision-and-language navigation: Interpreting visually-grounded navigation instructions in real environments. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3674\u20133683 (2018)","DOI":"10.1109\/CVPR.2018.00387"},{"issue":"2","key":"19_CR2","first-page":"28","volume":"11","author":"F Arena","year":"2022","unstructured":"Arena, F., Collotta, M., Pau, G., Termine, F.: An overview of augmented reality. Computers 11(2), 28 (2022)","journal-title":"An overview of augmented reality. Computers"},{"key":"19_CR3","doi-asserted-by":"crossref","unstructured":"Charatan, D., Li, S.L., Tagliasacchi, A., Sitzmann, V.: pixelsplat: 3d gaussian splats from image pairs for scalable generalizable 3d reconstruction. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 19457\u201319467 (2024)","DOI":"10.1109\/CVPR52733.2024.01840"},{"key":"19_CR4","doi-asserted-by":"crossref","unstructured":"Chen, Y., et al.: MVSPLAT: efficient 3d gaussian splatting from sparse multi-view images. In: European Conference on Computer Vision (ECCV), pp. 370\u2013386. Springer (2024)","DOI":"10.1007\/978-3-031-72664-4_21"},{"key":"19_CR5","doi-asserted-by":"crossref","unstructured":"Dai, A., Chang, A.X., Savva, M., Halber, M., Funkhouser, T., Nie\u00dfner, M.: Scannet: richly-annotated 3d reconstructions of indoor scenes. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2017)","DOI":"10.1109\/CVPR.2017.261"},{"key":"19_CR6","doi-asserted-by":"crossref","unstructured":"Dai, Z., Liu, T., Zhang, Y.: Efficient decoupled feature 3d gaussian splatting via hierarchical compression. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 11156\u201311166 (2025)","DOI":"10.1109\/CVPR52734.2025.01042"},{"key":"19_CR7","doi-asserted-by":"publisher","first-page":"40212","DOI":"10.52202\/079017-1271","volume":"37","author":"Z Fan","year":"2024","unstructured":"Fan, Z., et al.: Large spatial model: end-to-end unposed images to semantic 3d. Adv. Neural Inf. Process. Syst. (NeurIPS) 37, 40212\u201340229 (2024)","journal-title":"Adv. Neural Inf. Process. Syst. (NeurIPS)"},{"key":"19_CR8","unstructured":"Hong, S., Jung, J., Shin, H., Han, J., Yang, J., Luo, C., Kim, S.: Pf3plat: posefree feed-forward 3d gaussian splatting for novel view synthesis. In: International Conference on Machine Learning (ICML), vol. 267, pp. 23662\u201323681. PMLR (2025)"},{"key":"19_CR9","doi-asserted-by":"crossref","unstructured":"Huang, C., Mees, O., Zeng, A., Burgard, W.: Visual language maps for robot navigation. In: IEEE International Conference on Robotics and Automation (ICRA), pp. 10608\u201310615. IEEE (2023)","DOI":"10.1109\/ICRA48891.2023.10160969"},{"key":"19_CR10","doi-asserted-by":"crossref","unstructured":"Huang, R., Mikolajczyk, K.: No pose at all: Self-supervised pose-free 3d gaussian splatting from sparse views. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV), pp. 27947\u201327957 (2025)","DOI":"10.1109\/ICCV51701.2025.02594"},{"key":"19_CR11","doi-asserted-by":"crossref","unstructured":"Ji, Y., et al.: FASTLGS: speeding up language embedded gaussians with feature grid mapping. In: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), vol. 39, pp. 3922\u20133930 (2025)","DOI":"10.1609\/aaai.v39i4.32410"},{"issue":"6","key":"19_CR12","first-page":"1","volume":"44","author":"L Jiang","year":"2025","unstructured":"Jiang, L., et al.: Anysplat: Feed-forward 3d gaussian splatting from unconstrained views. ACM Trans. Graph. (TOG) 44(6), 1\u201316 (2025)","journal-title":"ACM Trans. Graph. (TOG)"},{"key":"19_CR13","doi-asserted-by":"crossref","unstructured":"Kang, G., et al.: Selfsplat: pose-free and 3d prior-free generalizable 3d gaussian splatting. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 22012\u201322022 (2025)","DOI":"10.1109\/CVPR52734.2025.02050"},{"key":"19_CR14","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), 139:1\u2013139:14 (2023)","DOI":"10.1145\/3592433"},{"key":"19_CR15","doi-asserted-by":"crossref","unstructured":"Leroy, V., Cabon, Y., Revaud, J.: Grounding image matching in 3d with mast3r. In: European Conference on Computer Vision (ECCV), pp. 71\u201391. Springer (2024)","DOI":"10.1007\/978-3-031-73220-1_5"},{"key":"19_CR16","unstructured":"Li, B., Weinberger, K.Q., Belongie, S., Koltun, V., Ranftl, R.: Language-driven semantic segmentation. In: International Conference on Learning Representations (ICLR) (2022)"},{"key":"19_CR17","unstructured":"Li, H., et\u00a0al.: IGGT: instance-grounded geometry transformer for semantic 3d reconstruction. arXiv preprint arXiv:2510.22706 (2025)"},{"issue":"4","key":"19_CR18","doi-asserted-by":"publisher","first-page":"741","DOI":"10.1007\/s41095-024-0430-4","volume":"10","author":"J Li","year":"2024","unstructured":"Li, J., et al.: Clip-SP: vision-language model with adaptive prompting for scene parsing. Comput. Visual Media 10(4), 741\u2013752 (2024)","journal-title":"Comput. Visual Media"},{"key":"19_CR19","unstructured":"Li, Q., Sun, J., An, L., Su, Z., Zhang, H., Liu, Y.: Semanticsplat: feed-forward 3d scene understanding with language-aware gaussian fields. arXiv preprint arXiv:2506.09565 (2025)"},{"key":"19_CR20","doi-asserted-by":"crossref","unstructured":"Li, W., Zhao, Y., Qin, M., Liu, Y., Cai, Y., Gan, C., Pfister, H.: Langsplatv2: high-dimensional 3d language gaussian splatting with 450+ FPS. In: Advances in Neural Information Processing Systems (NeurIPS) (2025)","DOI":"10.52202\/085713-5798"},{"key":"19_CR21","unstructured":"Lin, H., et al.: Depth anything 3: recovering the visual space from any views. arXiv preprint arXiv:2511.10647 (2025)"},{"key":"19_CR22","doi-asserted-by":"crossref","unstructured":"Liu, F., et al.: Langscene-x: reconstruct generalizable 3d language-embedded scenes with trimap video diffusion. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV), pp. 29010\u201329020 (2025)","DOI":"10.1109\/ICCV51701.2025.02694"},{"issue":"1","key":"19_CR23","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1145\/3503250","volume":"65","author":"B Mildenhall","year":"2021","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. Commun. ACM 65(1), 99\u2013106 (2021)","journal-title":"Commun. ACM"},{"key":"19_CR24","unstructured":"Oquab, M., et al.: Dinov2: learning robust visual features without supervision. arXiv preprint arXiv:2304.07193 (2023)"},{"key":"19_CR25","doi-asserted-by":"crossref","unstructured":"Qin, M., Li, W., Zhou, J., Wang, H., Pfister, H.: Langsplat: 3d language gaussian splatting. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 20051\u201320060 (2024)","DOI":"10.1109\/CVPR52733.2024.01895"},{"key":"19_CR26","unstructured":"Radford, A., et al.: Learning transferable visual models from natural language supervision. In: International Conference on Machine Learning (ICML), pp. 8748\u20138763. PMLR (2021)"},{"key":"19_CR27","doi-asserted-by":"crossref","unstructured":"Ranftl, R., Bochkovskiy, A., Koltun, V.: Vision transformers for dense prediction. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV), pp. 12179\u201312188 (2021)","DOI":"10.1109\/ICCV48922.2021.01196"},{"key":"19_CR28","unstructured":"Ravi, N., et al.: Sam 2: segment anything in images and videos. In: International Conference on Learning Representations (ICLR) (2025)"},{"key":"19_CR29","unstructured":"Shen, W., Yang, G., Yu, A., Wong, J., Kaelbling, L.P., Isola, P.: Distilled feature fields enable few-shot language-guided manipulation. In: Conference on Robot Learning (CoRL), pp. 405\u2013424. (2023) PMLR"},{"key":"19_CR30","doi-asserted-by":"crossref","unstructured":"Sheng, Y., Deng, J., Zhang, X., Zhang, Y., Hua, B., Zhang, Y., Ji, J.: Spatialsplat: efficient semantic 3d from sparse unposed images. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV), pp. 26404\u201326414 (2025)","DOI":"10.1109\/ICCV51701.2025.02450"},{"key":"19_CR31","doi-asserted-by":"crossref","unstructured":"Shi, J.C., Wang, M., Duan, H.B., Guan, S.H.: Language embedded 3d gaussians for open-vocabulary scene understanding. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 5333\u20135343. (2024)","DOI":"10.1109\/CVPR52733.2024.00510"},{"key":"19_CR32","unstructured":"Smart, B., Zheng, C., Laina, I., Prisacariu, V.A.: Splatt3r: zero-shot gaussian splatting from uncalibrated image pairs. arXiv preprint arXiv:2408.13912 (2024)"},{"key":"19_CR33","unstructured":"Stone, A., et al.: Open-world object manipulation using pre-trained vision-language models. In: Conference on Robot Learning (CoRL), pp. 3397\u20133417. PMLR (2023)"},{"key":"19_CR34","unstructured":"Sun, X., et\u00a0al.: Uni3r: unified 3d reconstruction and semantic understanding via generalizable gaussian splatting from unposed multi-view images. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 33280\u201333290 (2026)"},{"key":"19_CR35","unstructured":"Tian, Q., Tan, X., Gong, J., Xie, Y., Ma, L.: Uniforward: unified 3d scene and semantic field reconstruction via feed-forward gaussian splatting from only sparseview images. arXiv preprint arXiv:2506.09378 (2025)"},{"key":"19_CR36","doi-asserted-by":"crossref","unstructured":"Tian, Q., Tan, X., Xie, Y., Ma, L.: Drivingforward: feed-forward 3d gaussian splatting for driving scene reconstruction from flexible surround-view input. In: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI). vol. 39, pp. 7374\u20137382 (2025)","DOI":"10.1609\/aaai.v39i7.32793"},{"key":"19_CR37","doi-asserted-by":"crossref","unstructured":"Wang, J., Chen, M., Karaev, N., Vedaldi, A., Rupprecht, C., Novotny, D.: VGGT: visual geometry grounded transformer. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 5294\u20135306 (2025)","DOI":"10.1109\/CVPR52734.2025.00499"},{"key":"19_CR38","doi-asserted-by":"crossref","unstructured":"Wang, Q., Zhang, Y., Holynski, A., Efros, A.A., Kanazawa, A.: Continuous 3d perception model with persistent state. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2025)","DOI":"10.1109\/CVPR52734.2025.00983"},{"key":"19_CR39","doi-asserted-by":"crossref","unstructured":"Wang, S., Leroy, V., Cabon, Y., Chidlovskii, B., Revaud, J.: Dust3r: geometric 3d vision made easy. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 20697\u201320709 (2024)","DOI":"10.1109\/CVPR52733.2024.01956"},{"key":"19_CR40","unstructured":"Wang, X., Lan, C., Zhu, H., Chen, Z., Lu, Y.: Gsemsplat: generalizable semantic 3d gaussian splatting from uncalibrated image pairs. arXiv preprint arXiv:2412.16932 (2024)"},{"issue":"4","key":"19_CR41","doi-asserted-by":"publisher","first-page":"613","DOI":"10.1007\/s41095-024-0436-y","volume":"10","author":"T Wu","year":"2024","unstructured":"Wu, T., et al.: Recent advances in 3d gaussian splatting. Comput. Visual Media 10(4), 613\u2013642 (2024)","journal-title":"Comput. Visual Media"},{"key":"19_CR42","doi-asserted-by":"publisher","first-page":"19114","DOI":"10.52202\/079017-0604","volume":"37","author":"Y Wu","year":"2024","unstructured":"Wu, Y., et al.: Opengaussian: towards point-level 3d gaussian-based open vocabulary understanding. Adv. Neural Inf. Process. Syst. (NeurIPS) 37, 19114\u201319138 (2024)","journal-title":"Adv. Neural Inf. Process. Syst. (NeurIPS)"},{"issue":"1","key":"19_CR43","doi-asserted-by":"publisher","first-page":"83","DOI":"10.26599\/CVM.2025.9450383","volume":"11","author":"YQ Yang","year":"2025","unstructured":"Yang, Y.Q., et al.: Swin3d: a pretrained transformer backbone for 3d indoor scene understanding. Comput. Visual Media 11(1), 83\u2013101 (2025)","journal-title":"Comput. Visual Media"},{"key":"19_CR44","unstructured":"Ye, B., et al.: No pose, no problem: surprisingly simple 3d gaussian splats from sparse unposed images. In: International Conference on Learning Representations (ICLR), vol. 2025, pp. 54009\u201354033 (2025)"},{"key":"19_CR45","doi-asserted-by":"crossref","unstructured":"Yeshwanth, C., Liu, Y.C., Nie\u00dfner, M., Dai, A.: Scannet++: a high-fidelity dataset of 3d indoor scenes. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV), pp. 12\u201322 (2023)","DOI":"10.1109\/ICCV51070.2023.00008"},{"key":"19_CR46","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: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 586\u2013595. (2018)","DOI":"10.1109\/CVPR.2018.00068"},{"key":"19_CR47","doi-asserted-by":"crossref","unstructured":"Zhang, S., et al.: Flare: feed-forward geometry, appearance and camera estimation from uncalibrated sparse views. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 21936\u201321947 (2025)","DOI":"10.1109\/CVPR52734.2025.02043"},{"key":"19_CR48","doi-asserted-by":"crossref","unstructured":"Zhao, H., Jiang, L., Jia, J., Torr, P.H., Koltun, V.: Point transformer. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV), pp. 16259\u201316268 (2021)","DOI":"10.1109\/ICCV48922.2021.01595"},{"key":"19_CR49","doi-asserted-by":"crossref","unstructured":"Zhou, S., et al.: Feature 3dgs: supercharging 3d gaussian splatting to enable distilled feature fields. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 21676\u201321685 (2024)","DOI":"10.1109\/CVPR52733.2024.02048"}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ECCV 2026"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-37383-0_19","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,14]],"date-time":"2026-09-14T08:28:45Z","timestamp":1789374525000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-37383-0_19"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"ISBN":["9783032373823","9783032373830"],"references-count":49,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-37383-0_19","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]},"assertion":[{"value":"15 September 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ECCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"European Conference on Computer Vision","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Malm\u00f6","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Sweden","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2026","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 September 2026","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 September 2026","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":"eccv2026","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/eccv.ecva.net\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}