{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,19]],"date-time":"2025-12-19T19:10:59Z","timestamp":1766171459779,"version":"3.48.0"},"reference-count":60,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"MUR Progetti di Ricerca di Rilevante Interesse Nazionale","award":["2022YTE579"],"award-info":[{"award-number":["2022YTE579"]}]},{"name":"MUR Progetti di Ricerca di Rilevante Interesse Nazionale","award":["CUP G53D23002930006"],"award-info":[{"award-number":["CUP G53D23002930006"]}]},{"name":"Next-Generation EU - M4 C2 I1.1"},{"name":"Department Strategic Plan of the University of Udine"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Multimedia"],"published-print":{"date-parts":[[2025]]},"DOI":"10.1109\/tmm.2025.3613176","type":"journal-article","created":{"date-parts":[[2025,9,22]],"date-time":"2025-09-22T17:45:19Z","timestamp":1758563119000},"page":"9581-9591","source":"Crossref","is-referenced-by-count":0,"title":["ALCER3D: Adaptive Learning Constraints for Enhanced Retrieval of Complex Indoor 3D Scenarios"],"prefix":"10.1109","volume":"27","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6325-9066","authenticated-orcid":false,"given":"Alex","family":"Falcon","sequence":"first","affiliation":[{"name":"University of Udine, Udine, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4482-0479","authenticated-orcid":false,"given":"Ali","family":"Abdari","sequence":"additional","affiliation":[{"name":"University of Udine, Udine, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4269-4501","authenticated-orcid":false,"given":"Giuseppe","family":"Serra","sequence":"additional","affiliation":[{"name":"University of Udine, Udine, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.5325\/intelitestud.19.1.0017"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/VRW55335.2022.00043"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2016.2639380"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2013.2280560"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TLT.2023.3277952"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TLT.2023.3276760"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2024.3372591"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-20893-6_7"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW60793.2023.00217"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/WACV57701.2024.00571"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00120"},{"key":"ref12","article-title":"UNI3D: Exploring unified 3D representation at scale","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Zhou","year":"2024"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW60793.2023.00464"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/3652583.3658039"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-53302-0_7"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1145\/3606040.3617445"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-53311-2_35"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1142\/S0218001493000339"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2006.100"},{"key":"ref20","first-page":"8748","article-title":"Learning transferable visual models from natural language supervision","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Radford","year":"2021"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298682"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01075"},{"key":"ref23","first-page":"73","article-title":"SHREC13 track: Retrieval on textured 3D models","volume-title":"Proc. 6th Eurographics Workshop 3D Object Retrieval","author":"Cerri","year":"2013"},{"key":"ref24","first-page":"89","article-title":"SHREC13 track: Large scale sketch-based 3D shape retrieval","volume-title":"Proc. 6th Eurographics Workshop Object Retrieval","author":"Li","year":"2013"},{"key":"ref25","first-page":"65","article-title":"SHREC13 track: Retrieval of objects captured with low-cost depth-sensing cameras","volume-title":"Proc. 6th Eurographics Workshop Object Retrieval","author":"Machado","year":"2013"},{"key":"ref26","first-page":"81","article-title":"SHREC13 track: Large-scale partial shape retrieval using simulated range images","volume-title":"Proc. 6th Eurographics Workshop Object Retrieval","author":"Sipiran","year":"2013"},{"key":"ref27","article-title":"SHREC19 track: Extended 2D scene image-based 3D scene retrieval","volume":"700","author":"Abdul-Rashid","year":"2019","journal-title":"Training"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.02045"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/j.cag.2022.07.020"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.cag.2023.07.026"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1016\/j.cag.2023.07.035"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1016\/j.cag.2021.07.007"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1016\/j.cag.2022.07.015"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1016\/j.jmgm.2021.108103"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/j.cag.2021.06.010"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00007"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2025.129590"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2023.102033"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/tcsvt.2025.3551084"},{"key":"ref40","first-page":"44860","article-title":"Openshape: Scaling up 3D shape representation towards open-world understanding","volume-title":"Proc. Adv. neural Inf. Process. Syst.","author":"Liu","year":"2023"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.5555\/3524938.3525087"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00975"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.145"},{"key":"ref44","first-page":"1857","article-title":"Improved deep metric learning with multi-class n-pair loss objective","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Sohn","year":"2016"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33019243"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00758"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1145\/3343031.3351030"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1145\/3404835.3462927"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1145\/3512527.3531395"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.2010.11929"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1706.03762"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-11012-3_52"},{"key":"ref53","first-page":"25278","article-title":"LAION-5B: An open large-scale dataset for training next generation image-text models","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"2022","author":"Schuhmann"},{"article-title":"RoBERTa: A robustly optimized BERT pretraining approach","year":"2019","author":"Liu","key":"ref54"},{"key":"ref55","article-title":"DistilBERT, a distilled version of BERT: Smaller, faster, cheaper and lighter","volume-title":"Proc. Energy Efficient Mach. Learn. Cogn. Comput. Workshop","author":"Sanh","year":"2019"},{"key":"ref56","first-page":"5776","article-title":"MiniLM: Deep self-attention distillation for task-agnostic compression of pre-trained transformers","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"2020","author":"Wang"},{"article-title":"Towards general text embeddings with multi-stage contrastive learning","year":"2023","author":"Li","key":"ref57"},{"article-title":"CodeSearchNet challenge: Evaluating the state of semantic code search","year":"2019","author":"Husain","key":"ref58"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2020.2985716"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.3390\/s23208437"}],"container-title":["IEEE Transactions on Multimedia"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6046\/10844992\/11175509.pdf?arnumber=11175509","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,19]],"date-time":"2025-12-19T18:59:37Z","timestamp":1766170777000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11175509\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":60,"URL":"https:\/\/doi.org\/10.1109\/tmm.2025.3613176","relation":{},"ISSN":["1520-9210","1941-0077"],"issn-type":[{"type":"print","value":"1520-9210"},{"type":"electronic","value":"1941-0077"}],"subject":[],"published":{"date-parts":[[2025]]}}}