{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,4]],"date-time":"2026-07-04T20:14:54Z","timestamp":1783196094518,"version":"3.54.6"},"reference-count":137,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Neurocomputing"],"published-print":{"date-parts":[[2026,10]]},"DOI":"10.1016\/j.neucom.2026.134248","type":"journal-article","created":{"date-parts":[[2026,6,14]],"date-time":"2026-06-14T18:20:50Z","timestamp":1781461250000},"page":"134248","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["From closed sets to dynamic worlds: A comprehensive survey of open world object detection"],"prefix":"10.1016","volume":"698","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-8049-7722","authenticated-orcid":false,"given":"Yunong","family":"Gan","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoli","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaogang","family":"Lin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hao","family":"Pan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kangwei","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zilong","family":"Yin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.neucom.2026.134248_bib0005","series-title":"Proceedings of the 30th ACM International Conference on Multimedia (MM \u201922)","first-page":"1279","article-title":"Rethinking open-world object detection in autonomous driving scenarios","author":"Ma","year":"2022"},{"key":"10.1016\/j.neucom.2026.134248_bib0010","doi-asserted-by":"crossref","DOI":"10.3390\/app132312806","article-title":"A parallel open-world object detection framework with uncertainty mitigation for campus monitoring","volume":"13","author":"Dong","year":"2023","journal-title":"Appl. Sci."},{"key":"10.1016\/j.neucom.2026.134248_bib0015","doi-asserted-by":"crossref","DOI":"10.1016\/j.image.2021.116224","article-title":"AFLNet: adversarial focal loss network for RGB-D salient object detection","volume":"94","author":"Zhao","year":"2021","journal-title":"Signal Process. Image Commun."},{"key":"10.1016\/j.neucom.2026.134248_bib0020","doi-asserted-by":"crossref","first-page":"1137","DOI":"10.1109\/TPAMI.2016.2577031","article-title":"Faster R-CNN: towards real-time object detection with region proposal networks","volume":"39","author":"Ren","year":"2017","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.neucom.2026.134248_bib0025","series-title":"2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"779","article-title":"You only look once: unified, real-time object detection","author":"Redmon","year":"2016"},{"key":"10.1016\/j.neucom.2026.134248_bib0030","series-title":"Computer Vision \u2013 ECCV 2016","first-page":"21","article-title":"SSD: single shot MultiBox detector","author":"Liu","year":"2016"},{"key":"10.1016\/j.neucom.2026.134248_bib0035","series-title":"Computer Vision \u2013 ECCV 2020","first-page":"213","article-title":"End-to-end object detection with transformers","author":"Carion","year":"2020"},{"key":"10.1016\/j.neucom.2026.134248_bib0040","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1016\/j.neucom.2020.01.085","article-title":"Recent advances in deep learning for object detection","volume":"396","author":"Wu","year":"2020","journal-title":"Neurocomputing"},{"key":"10.1016\/j.neucom.2026.134248_bib0045","doi-asserted-by":"crossref","first-page":"988","DOI":"10.1109\/TCSVT.2024.3480691","article-title":"Open world object detection: a survey","volume":"35","author":"Li","year":"2025","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.neucom.2026.134248_bib0050","series-title":"2021 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"5826","article-title":"Towards open world object detection","author":"Joseph","year":"2021"},{"key":"10.1016\/j.neucom.2026.134248_bib0055","doi-asserted-by":"crossref","first-page":"154","DOI":"10.37256\/aie.4220233058","article-title":"A framework for open world object detection","author":"Shaheen","year":"2023","journal-title":"Artif. Intell. Evol."},{"key":"10.1016\/j.neucom.2026.134248_bib0060","series-title":"Proceedings of the 3rd International Workshop on Human-Centric Multimedia Analysis","first-page":"35","article-title":"Two-branch objectness-centric open world detection","author":"Wu","year":"2022"},{"key":"10.1016\/j.neucom.2026.134248_bib0065","doi-asserted-by":"crossref","first-page":"3496","DOI":"10.1109\/TCSVT.2023.3326279","article-title":"Revisiting open world object detection","volume":"34","author":"Zhao","year":"2024","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.neucom.2026.134248_bib0070","doi-asserted-by":"crossref","unstructured":"Z. Wu, Y. Lu, X. Chen, Z. Wu, L. Kang, J. Yu, UC-OWOD: unknown-classified open world object detection, 2022, https:\/\/arxiv.org\/abs\/2207.11455","DOI":"10.1007\/978-3-031-20080-9_12"},{"key":"10.1016\/j.neucom.2026.134248_bib0075","series-title":"2023 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"11454","article-title":"Annealing-based label-transfer learning for open world object detection","author":"Ma","year":"2023"},{"key":"10.1016\/j.neucom.2026.134248_bib0080","series-title":"2025 IEEE\/CVF Winter Conference on Applications of Computer Vision (WACV)","first-page":"8207","article-title":"Decoupled PROB: decoupled query initialization tasks and objectness-class learning for open world object detection","author":"Inoue","year":"2025"},{"key":"10.1016\/j.neucom.2026.134248_bib0085","series-title":"Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2001), 1","article-title":"Rapid object detection using a boosted cascade of simple features","author":"Viola","year":"2001"},{"key":"10.1016\/j.neucom.2026.134248_bib0090","series-title":"2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"6154","article-title":"Cascade R-CNN: delving into high quality object detection","author":"Cai","year":"2018"},{"key":"10.1016\/j.neucom.2026.134248_bib0095","series-title":"2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition","first-page":"2241","article-title":"Cascade object detection with deformable part models","author":"Felzenszwalb","year":"2010"},{"key":"10.1016\/j.neucom.2026.134248_bib0100","unstructured":"S. Yang, P. Sun, Y. Jiang, X. Xia, R. Zhang, Z. Yuan, C. Wang, P. Luo, M. Xu, Objects in semantic topology, 2022, https:\/\/arxiv.org\/abs\/2110.02687"},{"key":"10.1016\/j.neucom.2026.134248_bib0105","series-title":"Computer Vision \u2013 ECCV 2022","first-page":"268","article-title":"Learning to detect every thing in an open world","author":"Saito","year":"2022"},{"key":"10.1016\/j.neucom.2026.134248_bib0110","series-title":"2022 IEEE International Conference on Image Processing (ICIP)","first-page":"626","article-title":"Open-world object detection via discriminative class prototype learning","author":"Yu","year":"2022"},{"key":"10.1016\/j.neucom.2026.134248_bib0115","unstructured":"H. Huang, A. Geiger, D. Zhang, GOOD: exploring geometric cues for detecting objects in an open world, 2023, https:\/\/arxiv.org\/abs\/2212.11720"},{"key":"10.1016\/j.neucom.2026.134248_bib0120","unstructured":"R. Fang, G. Pang, L. Zhou, X. Bai, J. Zheng, Unsupervised recognition of unknown objects for open-world object detection, 2023, https:\/\/arxiv.org\/abs\/2308.16527"},{"key":"10.1016\/j.neucom.2026.134248_bib0125","series-title":"2023 IEEE\/CVF International Conference on Computer Vision (ICCV)","first-page":"6210","article-title":"Random boxes are open-world object detectors","author":"Wang","year":"2023"},{"key":"10.1016\/j.neucom.2026.134248_bib0130","doi-asserted-by":"crossref","unstructured":"W. Liang, F. Xue, Y. Liu, G. Zhong, A. Ming, Unknown sniffer for object detection: don\u2019t turn a blind eye to unknown objects, 2023, https:\/\/arxiv.org\/abs\/2303.13769","DOI":"10.1109\/CVPR52729.2023.00315"},{"key":"10.1016\/j.neucom.2026.134248_bib0135","unstructured":"D. Pershouse, F. Dayoub, D. Miller, N. S\u00fcnderhauf, Addressing the challenges of open-world object detection, 2023, https:\/\/arxiv.org\/abs\/2303.14930"},{"key":"10.1016\/j.neucom.2026.134248_bib0140","series-title":"Advances in Neural Information Processing Systems, 37","first-page":"74233","article-title":"UMB: understanding model behavior for open-world object detection","author":"Xi","year":"2024"},{"key":"10.1016\/j.neucom.2026.134248_bib0145","series-title":"Pattern Recognition and Computer Vision: 7th Chinese Conference, PRCV 2024, Urumqi, China, October 18\u201320, 2024, Proceedings, Part XII","first-page":"78","article-title":"Class-agnostic detection of unknown objects from foreground improves robust open world object detection","author":"Zhao","year":"2024"},{"key":"10.1016\/j.neucom.2026.134248_bib0150","series-title":"Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence (IJCAI-24)","first-page":"1462","article-title":"KTCN: enhancing open-world object detection with knowledge transfer and class-awareness neutralization","author":"Xi","year":"2024"},{"key":"10.1016\/j.neucom.2026.134248_bib0155","doi-asserted-by":"crossref","first-page":"609","DOI":"10.26599\/TST.2024.9010263","article-title":"UMLN: open-world object detection empowered by unsupervised modeling and location-enhanced network","volume":"31","author":"Huang","year":"2026","journal-title":"Tsinghua Sci. Technol."},{"key":"10.1016\/j.neucom.2026.134248_bib0160","doi-asserted-by":"crossref","first-page":"729","DOI":"10.1109\/TIP.2024.3459589","article-title":"Recalling unknowns without losing precision: an effective solution to large model-guided open world object detection","volume":"34","author":"He","year":"2025","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.neucom.2026.134248_bib0165","article-title":"Text-guided unknown pseudo-labeling for open-world object detection","volume":"13","author":"Wang","year":"2024","journal-title":"Electronics"},{"key":"10.1016\/j.neucom.2026.134248_bib0170","series-title":"2024 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"17302","article-title":"Exploring orthogonality in open world object detection","author":"Sun","year":"2024"},{"key":"10.1016\/j.neucom.2026.134248_bib0175","doi-asserted-by":"crossref","first-page":"3395","DOI":"10.1109\/TCSVT.2023.3322465","article-title":"Instance-dictionary learning for open-world object detection in autonomous driving scenarios","volume":"34","author":"Ma","year":"2024","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.neucom.2026.134248_bib0180","first-page":"694","article-title":"OW-adapter: human-assisted open-world object detection with a few examples","volume":"30","author":"Jamonnak","year":"2024","journal-title":"IEEE Trans. Vis. Comput. Graph."},{"key":"10.1016\/j.neucom.2026.134248_bib0185","unstructured":"G. Allabadi, A. Lucic, S. Aananth, T. Yang, Y.-X. Wang, V. Adve, Generalized open-world semi-supervised object detection, 2024, https:\/\/arxiv.org\/abs\/2307.15710"},{"key":"10.1016\/j.neucom.2026.134248_bib0190","series-title":"2025 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"20318","article-title":"Detecting open world objects via partial attribute assignment","author":"Yang","year":"2025"},{"key":"10.1016\/j.neucom.2026.134248_bib0195","doi-asserted-by":"crossref","first-page":"9686","DOI":"10.1109\/TMM.2025.3618534","article-title":"Causality-inspired debiasing learning for open world object detection","volume":"27","author":"Zhao","year":"2025","journal-title":"IEEE Trans. Multimed."},{"key":"10.1016\/j.neucom.2026.134248_bib0200","doi-asserted-by":"crossref","DOI":"10.1016\/j.neunet.2025.108501","article-title":"Hunting for the unknown: open world object detection from a class-agnostic perspective","volume":"197","author":"Wang","year":"2026","journal-title":"Neural Netw."},{"key":"10.1016\/j.neucom.2026.134248_bib0205","series-title":"Advanced Intelligent Computing Technology and Applications","first-page":"63","article-title":"Decoupled modeling of foreground and background for open-world object detection","author":"Ye","year":"2025"},{"key":"10.1016\/j.neucom.2026.134248_bib0210","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2025.127050","article-title":"FMDL: enhancing open-world object detection with foundation models and dynamic learning","volume":"275","author":"Huang","year":"2025","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.neucom.2026.134248_bib0215","series-title":"2025 IEEE International Conference on Multimedia and Expo (ICME)","first-page":"1","article-title":"DLLM: enhancing open-world object detection with dynamic learning and large models","author":"Huang","year":"2025"},{"key":"10.1016\/j.neucom.2026.134248_bib0220","doi-asserted-by":"crossref","first-page":"296","DOI":"10.1007\/s44443-025-00329-3","article-title":"Semi-supervised contrastive clustering with strong-weak augmentation for novel class discovery in open-world object detection","volume":"37","author":"Wang","year":"2025","journal-title":"J. King Saud Univ. Comput. Inf. Sci."},{"key":"10.1016\/j.neucom.2026.134248_bib0225","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2025.129375","article-title":"SALLM: open world object detection empowered by self adaptive learning and large model","volume":"297","author":"Huang","year":"2026","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.neucom.2026.134248_bib0230","doi-asserted-by":"crossref","DOI":"10.1016\/j.imavis.2025.105508","article-title":"DDMCB: open-world object detection empowered by denoising diffusion models and calibration balance","volume":"157","author":"Huang","year":"2025","journal-title":"Image Vis. Comput."},{"key":"10.1016\/j.neucom.2026.134248_bib0235","doi-asserted-by":"crossref","DOI":"10.1007\/s10586-025-05161-y","article-title":"Region-aware unknown information enhancement for open world object detection","volume":"28","author":"Su","year":"2025","journal-title":"Clust. Comput."},{"key":"10.1016\/j.neucom.2026.134248_bib0240","unstructured":"A. Majee, A. Gangrade, R. Iyer, Looking beyond the known: towards a data discovery guided open-world object detection, 2025, https:\/\/arxiv.org\/abs\/2510.00303"},{"key":"10.1016\/j.neucom.2026.134248_bib0245","series-title":"2022 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"9225","article-title":"OW-DETR: open-world detection transformer","author":"Gupta","year":"2022"},{"key":"10.1016\/j.neucom.2026.134248_bib0250","doi-asserted-by":"crossref","unstructured":"S. Ma, Y. Wang, J. Fan, Y. Wei, T.H. Li, H. Liu, F. Lv, CAT: LoCalization and IdentificAtion cascade detection transformer for open-world object detection, 2023, https:\/\/arxiv.org\/abs\/2301.01970","DOI":"10.1109\/CVPR52729.2023.01885"},{"key":"10.1016\/j.neucom.2026.134248_bib0255","series-title":"2023 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"11444","article-title":"PROB: probabilistic objectness for open world object detection","author":"Zohar","year":"2023"},{"key":"10.1016\/j.neucom.2026.134248_bib0260","doi-asserted-by":"crossref","unstructured":"L. Yao, J. Han, Y. Wen, X. Liang, D. Xu, W. Zhang, Z. Li, C. Xu, H. Xu, DetCLIP: dictionary-enriched visual-concept paralleled pre-training for open-world detection, 2022, https:\/\/arxiv.org\/abs\/2209.09407","DOI":"10.52202\/068431-0663"},{"key":"10.1016\/j.neucom.2026.134248_bib0265","unstructured":"N. Dong, Y. Zhang, M. Ding, G.H. Lee, Open world DETR: transformer based open world object detection, 2022, https:\/\/arxiv.org\/abs\/2212.02969"},{"key":"10.1016\/j.neucom.2026.134248_bib0270","unstructured":"S. Ma, Y. Wang, Y. Wei, J. Fan, E. Zhang, X. Sun, P. Chen, SKDF: a simple knowledge distillation framework for distilling open-vocabulary knowledge to open-world object detector, 2024, https:\/\/arxiv.org\/abs\/2312.08653"},{"key":"10.1016\/j.neucom.2026.134248_bib0275","unstructured":"O. Zohar, A. Lozano, S. Goel, S. Yeung, K.-C. Wang, Open world object detection in the era of foundation models, 2023, https:\/\/arxiv.org\/abs\/2312.05745"},{"key":"10.1016\/j.neucom.2026.134248_bib0280","unstructured":"S. Ma, Y. Wang, Y. Wei, P. Chen, Z. Ye, J. Fan, E. Zhang, T.H. Li, Detecting the open-world objects with the help of the brain, 2023, https:\/\/arxiv.org\/abs\/2303.11623"},{"key":"10.1016\/j.neucom.2026.134248_bib0285","series-title":"2023 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"15233","article-title":"CapDet: unifying dense captioning and open-world detection pretraining","author":"Long","year":"2023"},{"key":"10.1016\/j.neucom.2026.134248_bib0290","doi-asserted-by":"crossref","unstructured":"T. Doan, X. Li, S. Behpour, W. He, L. Gou, L. Ren, Hyp-OW: exploiting hierarchical structure learning with hyperbolic distance enhances open world object detection, 2024, https:\/\/arxiv.org\/abs\/2306.14291","DOI":"10.1609\/aaai.v38i2.27921"},{"key":"10.1016\/j.neucom.2026.134248_bib0295","doi-asserted-by":"crossref","unstructured":"Z. Wang, Y. Li, X. Chen, S.-N. Lim, A. Torralba, H. Zhao, S. Wang, Detecting everything in the open world: towards universal object detection, 2023, https:\/\/arxiv.org\/abs\/2303.11749","DOI":"10.1109\/CVPR52729.2023.01100"},{"key":"10.1016\/j.neucom.2026.134248_bib0300","series-title":"Generalizing From Limited Resources in the Open World","first-page":"165","article-title":"Semantic-degrade learning framework for open world object detection","author":"He","year":"2024"},{"key":"10.1016\/j.neucom.2026.134248_bib0305","unstructured":"S. Lee, M. Jeon, J. Min, J. Seo, OW-rep: open world object detection with instance representation learning, 2025, https:\/\/arxiv.org\/abs\/2409.16073"},{"key":"10.1016\/j.neucom.2026.134248_bib0310","first-page":"7762","article-title":"OV-DQUO: open-vocabulary DETR with denoising text query training and open-world unknown objects supervision","volume":"39","author":"Wang","year":"2025","journal-title":"Proc. AAAI Conf. Artif. Intell."},{"key":"10.1016\/j.neucom.2026.134248_bib0315","unstructured":"B. Dong, Z. Huang, G. Yang, L. Zhang, W. Zuo, MR-GDINO: efficient open-world continual object detection, 2024, https:\/\/arxiv.org\/abs\/2412.15979"},{"key":"10.1016\/j.neucom.2026.134248_bib0320","first-page":"4305","article-title":"Semi-supervised open-world object detection","volume":"38","author":"Mullappilly","year":"2024","journal-title":"Proc. AAAI Conf. Artif. Intell."},{"key":"10.1016\/j.neucom.2026.134248_bib0325","unstructured":"Y. Zhang, Y. Lu, J. Betz, TARO: toward semantically rich open-world object detection, 2025, https:\/\/arxiv.org\/abs\/2510.09173"},{"key":"10.1016\/j.neucom.2026.134248_bib0330","unstructured":"T. Ren, Y. Chen, Q. Jiang, Z. Zeng, Y. Xiong, W. Liu, Z. Ma, J. Shen, Y. Gao, X. Jiang, X. Chen, Z. Song, Y. Zhang, H. Huang, H. Gao, S. Liu, H. Zhang, F. Li, K. Yu, L. Zhang, DINO-X: a unified vision model for open-world object detection and understanding, 2025, https:\/\/arxiv.org\/abs\/2411.14347"},{"key":"10.1016\/j.neucom.2026.134248_bib0335","series-title":"2025 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"30332","article-title":"Open-world objectness modeling unifies novel object detection","author":"Zhang","year":"2025"},{"key":"10.1016\/j.neucom.2026.134248_bib0340","unstructured":"J. Duan, W. Xue, Z. Kang, S. Liu, J. Xia, OW-CLIP: data-efficient visual supervision for open-world object detection via Human-AI collaboration, 2025, https:\/\/arxiv.org\/abs\/2507.19870"},{"key":"10.1016\/j.neucom.2026.134248_bib0345","unstructured":"Z. Lin, Y. Wang, VL-SAM-V2: open-world object detection with general and specific query fusion, 2025, https:\/\/arxiv.org\/abs\/2505.18986"},{"key":"10.1016\/j.neucom.2026.134248_bib0350","series-title":"2025 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"25454","article-title":"OW-OVD: unified open world and open vocabulary object detection","author":"Xi","year":"2025"},{"key":"10.1016\/j.neucom.2026.134248_bib0355","author":"Li"},{"key":"10.1016\/j.neucom.2026.134248_bib0360","unstructured":"L. Liu, J. Feng, H. Chen, A. Wang, L. Song, J. Han, G. Ding, YOLO-UniOW: efficient universal open-world object detection, 2024, https:\/\/arxiv.org\/abs\/2412.20645"},{"key":"10.1016\/j.neucom.2026.134248_bib0365","series-title":"2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"6517","article-title":"YOLO9000: better, faster, stronger","author":"Redmon","year":"2017"},{"key":"10.1016\/j.neucom.2026.134248_bib0370","series-title":"2024 International Conference on Advances in Data Engineering and Intelligent Computing Systems (ADICS)","first-page":"1","article-title":"YOLOv8: a novel object detection algorithm with enhanced performance and robustness","author":"Varghese","year":"2024"},{"key":"10.1016\/j.neucom.2026.134248_bib0375","doi-asserted-by":"crossref","unstructured":"A. Wang, H. Chen, L. Liu, K. Chen, Z. Lin, J. Han, G. Ding, YOLOv10: real-time end-to-end object detection, 2024, https:\/\/arxiv.org\/abs\/2405.14458","DOI":"10.52202\/079017-3429"},{"key":"10.1016\/j.neucom.2026.134248_bib0380","doi-asserted-by":"crossref","first-page":"3614","DOI":"10.1109\/TPAMI.2020.2981604","article-title":"Recent advances in open set recognition: a survey","volume":"43","author":"Geng","year":"2020","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.neucom.2026.134248_bib0385","series-title":"2021 IEEE Fourth International Conference on Artificial Intelligence and Knowledge Engineering (AIKE)","first-page":"37","article-title":"A survey on open set recognition","author":"Mahdavi","year":"2021"},{"key":"10.1016\/j.neucom.2026.134248_bib0390","doi-asserted-by":"crossref","DOI":"10.1007\/s10489-025-06956-7","article-title":"Recognizing unknowns: a survey on visual open-set recognition","volume":"55","author":"Li","year":"2025","journal-title":"Appl. Intell."},{"key":"10.1016\/j.neucom.2026.134248_bib0395","doi-asserted-by":"crossref","first-page":"6145","DOI":"10.1007\/s11263-025-02479-3","article-title":"Rethinking open-set object detection: issues, a new formulation, and taxonomy","volume":"133","author":"Hosoya","year":"2025","journal-title":"Int. J. Comput. Vis."},{"key":"10.1016\/j.neucom.2026.134248_bib0400","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1016\/j.neunet.2019.01.012","article-title":"Continual lifelong learning with neural networks: a review","volume":"113","author":"Parisi","year":"2019","journal-title":"Neural Netw."},{"key":"10.1016\/j.neucom.2026.134248_bib0405","doi-asserted-by":"crossref","first-page":"307","DOI":"10.1016\/j.neunet.2023.10.039","article-title":"A survey on few-shot class-incremental learning","volume":"169","author":"Tian","year":"2024","journal-title":"Neural Netw."},{"key":"10.1016\/j.neucom.2026.134248_bib0410","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1016\/j.neunet.2020.12.003","article-title":"A comprehensive study of class incremental learning algorithms for visual tasks","volume":"135","author":"Belouadah","year":"2021","journal-title":"Neural Netw."},{"key":"10.1016\/j.neucom.2026.134248_bib0415","doi-asserted-by":"crossref","first-page":"1150","DOI":"10.1109\/TCSVT.2024.3477951","article-title":"Class incremental learning with less forgetting direction and equilibrium point","volume":"35","author":"Wen","year":"2025","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.neucom.2026.134248_bib0420","unstructured":"A.-S. Bulzan, C. Cernazanu-Glavan, Towards open world detection: a survey, 2025, https:\/\/arxiv.org\/abs\/2508.16527"},{"key":"10.1016\/j.neucom.2026.134248_bib0425","doi-asserted-by":"crossref","first-page":"1757","DOI":"10.1109\/TPAMI.2012.256","article-title":"Toward open set recognition","volume":"35","author":"Scheirer","year":"2013","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.neucom.2026.134248_bib0430","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2024.110560","article-title":"Synthetic unknown class learning for learning unknowns","volume":"153","author":"Jang","year":"2024","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.neucom.2026.134248_bib0435","doi-asserted-by":"crossref","DOI":"10.1007\/s42979-020-0086-9","article-title":"Deep open set recognition using dynamic intra-class splitting","volume":"1","author":"Schlachter","year":"2020","journal-title":"SN Comput. Sci."},{"key":"10.1016\/j.neucom.2026.134248_bib0440","series-title":"2021 IEEE Fourth International Conference on Artificial Intelligence and Knowledge Engineering (AIKE)","first-page":"37","article-title":"A survey on open set recognition","author":"Mahdavi","year":"2021"},{"key":"10.1016\/j.neucom.2026.134248_bib0445","series-title":"2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"1563","article-title":"Towards open set deep networks","author":"Bendale","year":"2016"},{"key":"10.1016\/j.neucom.2026.134248_bib0450","doi-asserted-by":"crossref","first-page":"762","DOI":"10.1109\/TPAMI.2017.2707495","article-title":"The extreme value machine","volume":"40","author":"Rudd","year":"2018","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.neucom.2026.134248_bib0455","unstructured":"W. Liu, X. Wang, J.D. Owens, Y. Li, Energy-based out-of-distribution detection, 2021, https:\/\/arxiv.org\/abs\/2010.03759"},{"key":"10.1016\/j.neucom.2026.134248_bib0460","series-title":"2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"2302","article-title":"C2AE: class conditioned auto-encoder for open-set recognition","author":"Oza","year":"2019"},{"key":"10.1016\/j.neucom.2026.134248_bib0465","series-title":"2024 IEEE\/CVF Winter Conference on Applications of Computer Vision (WACV)","first-page":"218","article-title":"Open-set object detection by aligning known class representations","author":"Sarkar","year":"2024"},{"key":"10.1016\/j.neucom.2026.134248_bib0470","series-title":"Computer Vision \u2013 ECCV 2024 Workshops","first-page":"46","article-title":"Open-set object detection: towards unified problem formulation and benchmarking","author":"Ammar","year":"2025"},{"key":"10.1016\/j.neucom.2026.134248_bib0475","article-title":"Reducing network agnostophobia","volume":"31","author":"Dhamija","year":"2018","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.neucom.2026.134248_bib0480","series-title":"2018 IEEE International Conference on Robotics and Automation (ICRA)","first-page":"3243","article-title":"Dropout sampling for robust object detection in open-set conditions","author":"Miller","year":"2018"},{"key":"10.1016\/j.neucom.2026.134248_bib0485","series-title":"CVPR Workshops","first-page":"87","article-title":"Improving deep network robustness to unknown inputs with objectosphere","author":"Dhamija","year":"2019"},{"key":"10.1016\/j.neucom.2026.134248_bib0490","unstructured":"X. Du, Z. Wang, M. Cai, Y. Li, VOS: learning what you don\u2019t know by virtual outlier synthesis, 2022, https:\/\/arxiv.org\/abs\/2202.01197"},{"key":"10.1016\/j.neucom.2026.134248_bib0495","doi-asserted-by":"crossref","first-page":"1691","DOI":"10.1109\/LRA.2023.3242169","article-title":"Open-set object detection using classification-free object proposal and instance-level contrastive learning","volume":"8","author":"Zhou","year":"2023","journal-title":"IEEE Robot. Autom. Lett."},{"key":"10.1016\/j.neucom.2026.134248_bib0500","unstructured":"S. Liang, W. Wang, R. Chen, A. Liu, B. Wu, E.-C. Chang, X. Cao, D. Tao, Object detectors in the open environment: challenges, solutions, and outlook, 2024, https:\/\/arxiv.org\/abs\/2403.16271"},{"key":"10.1016\/j.neucom.2026.134248_bib0505","unstructured":"B.S.Y. Loke, F. Quadri, G. Vivanco, M. Casagrande, S. Fenollosa, Overcoming catastrophic forgetting in neural networks, 2025, https:\/\/arxiv.org\/abs\/2507.10485"},{"key":"10.1016\/j.neucom.2026.134248_bib0510","doi-asserted-by":"crossref","first-page":"9971","DOI":"10.1007\/s10489-024-05695-5","article-title":"Class-incremental learning via prototype similarity replay and similarity-adjusted regularization","volume":"54","author":"Chen","year":"2024","journal-title":"Appl. Intell."},{"key":"10.1016\/j.neucom.2026.134248_bib0515","unstructured":"Q. Wu, S. Zhang, D. Cheng, Y. Xing, D. Xu, P. Wang, Y. Zhang, Demystifying catastrophic forgetting in two-stage incremental object detector, 2025, https:\/\/arxiv.org\/abs\/2502.05540"},{"key":"10.1016\/j.neucom.2026.134248_bib0520","series-title":"2025 IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)","first-page":"6547","article-title":"Prototype-based continual learning with label-free replay buffer and cluster preservation loss","author":"Aghasanli","year":"2025"},{"key":"10.1016\/j.neucom.2026.134248_bib0525","series-title":"2017 IEEE International Conference on Computer Vision (ICCV)","first-page":"3420","article-title":"Incremental learning of object detectors without catastrophic forgetting","author":"Shmelkov","year":"2017"},{"key":"10.1016\/j.neucom.2026.134248_bib0530","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1016\/j.patrec.2020.09.030","article-title":"Faster ILOD: incremental learning for object detectors based on faster RCNN","volume":"140","author":"Peng","year":"2020","journal-title":"Pattern Recognit. Lett."},{"key":"10.1016\/j.neucom.2026.134248_bib0535","doi-asserted-by":"crossref","first-page":"4348","DOI":"10.1109\/TMM.2025.3535403","article-title":"Replay-based incremental object detection with local response exploration","volume":"27","author":"Zhong","year":"2025","journal-title":"IEEE Trans. Multimed."},{"key":"10.1016\/j.neucom.2026.134248_bib0540","series-title":"2022 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"9417","article-title":"Overcoming catastrophic forgetting in incremental object detection via elastic response distillation","author":"Feng","year":"2022"},{"key":"10.1016\/j.neucom.2026.134248_bib0545","doi-asserted-by":"crossref","DOI":"10.1016\/j.cviu.2021.103229","article-title":"SID: incremental learning for anchor-free object detection via selective and inter-related distillation","volume":"210","author":"Peng","year":"2021","journal-title":"Comput. Vis. Image Underst."},{"key":"10.1016\/j.neucom.2026.134248_bib0550","author":"Li"},{"key":"10.1016\/j.neucom.2026.134248_bib0555","doi-asserted-by":"crossref","first-page":"318","DOI":"10.1109\/TPAMI.2018.2858826","article-title":"Focal loss for dense object detection","volume":"42","author":"Lin","year":"2020","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.neucom.2026.134248_bib0560","series-title":"2019 IEEE\/CVF International Conference on Computer Vision (ICCV)","first-page":"9626","article-title":"FCOS: fully convolutional one-stage object detection","author":"Tian","year":"2019"},{"key":"10.1016\/j.neucom.2026.134248_bib0565","series-title":"2019 IEEE\/CVF International Conference on Computer Vision (ICCV)","first-page":"6568","article-title":"CenterNet: keypoint triplets for object detection","author":"Duan","year":"2019"},{"key":"10.1016\/j.neucom.2026.134248_bib0570","unstructured":"A. Radford, J.W. Kim, C. Hallacy, A. Ramesh, G. Goh, S. Agarwal, G. Sastry, A. Askell, P. Mishkin, J. Clark, G. Krueger, I. Sutskever, Learning transferable visual models from natural language supervision, 2021, https:\/\/arxiv.org\/abs\/2103.00020"},{"key":"10.1016\/j.neucom.2026.134248_bib0575","unstructured":"X. Zhu, W. Su, L. Lu, B. Li, X. Wang, J. Dai, Deformable DETR: deformable transformers for end-to-end object detection, 2021, https:\/\/arxiv.org\/abs\/2010.04159"},{"key":"10.1016\/j.neucom.2026.134248_bib0580","doi-asserted-by":"crossref","unstructured":"F. Li, H. Zhang, S. Liu, J. Guo, L.M. Ni, L. Zhang, DN-DETR: accelerate DETR training by introducing query DeNoising, 2022, https:\/\/arxiv.org\/abs\/2203.01305","DOI":"10.1109\/CVPR52688.2022.01325"},{"key":"10.1016\/j.neucom.2026.134248_bib0585","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2024.112414","article-title":"Pseudo-unknown uncertainty learning for open set object detection","volume":"303","author":"Han","year":"2024","journal-title":"Knowl.-based Syst."},{"key":"10.1016\/j.neucom.2026.134248_bib0590","unstructured":"M. Sensoy, L. Kaplan, M. Kandemir, Evidential deep learning to quantify classification uncertainty, 2018, https:\/\/arxiv.org\/abs\/1806.01768"},{"key":"10.1016\/j.neucom.2026.134248_bib0595","unstructured":"M. Oquab, T. Darcet, T. Moutakanni, H. Vo, M. Szafraniec, V. Khalidov, P. Fernandez, D. Haziza, F. Massa, A. El-Nouby, M. Assran, N. Ballas, W. Galuba, R. Howes, P.-Y. Huang, S.-W. Li, I. Misra, M. Rabbat, V. Sharma, G. Synnaeve, H. Xu, H. Jegou, J. Mairal, P. Labatut, A. Joulin, P. Bojanowski, DINOv2: learning robust visual features without supervision, 2024, https:\/\/arxiv.org\/abs\/2304.07193"},{"key":"10.1016\/j.neucom.2026.134248_bib0600","doi-asserted-by":"crossref","unstructured":"A. Kirillov, E. Mintun, N. Ravi, H. Mao, C. Rolland, L. Gustafson, T. Xiao, S. Whitehead, A.C. Berg, W.-Y. Lo, P. Doll\u00e1r, R. Girshick, Segment anything, 2023, https:\/\/arxiv.org\/abs\/2304.02643","DOI":"10.1109\/ICCV51070.2023.00371"},{"key":"10.1016\/j.neucom.2026.134248_bib0605","doi-asserted-by":"crossref","unstructured":"L. Yao, J. Han, X. Liang, D. Xu, W. Zhang, Z. Li, H. Xu, DetCLIPv2: scalable open-vocabulary object detection pre-training via word-region alignment, 2023, https:\/\/arxiv.org\/abs\/2304.04514","DOI":"10.1109\/CVPR52729.2023.02250"},{"key":"10.1016\/j.neucom.2026.134248_bib0610","series-title":"2022 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"10955","article-title":"Grounded language-image pre-training","author":"Li","year":"2022"},{"key":"10.1016\/j.neucom.2026.134248_bib0615","series-title":"Computer Vision \u2013 ECCV 2024: 18th European Conference, Milan, Italy, September 29\u2013October 4, 2024, Proceedings, Part LXXI","first-page":"196","article-title":"Towards open-world object-based anomaly detection via self-supervised outlier synthesis","author":"Isaac-Medina","year":"2024"},{"key":"10.1016\/j.neucom.2026.134248_bib0620","doi-asserted-by":"crossref","unstructured":"X. Du, X. Wang, G. Gozum, Y. Li, Unknown-aware object detection: learning what you don\u2019t know from videos in the wild, 2022, https:\/\/arxiv.org\/abs\/2203.03800","DOI":"10.1109\/CVPR52688.2022.01331"},{"key":"10.1016\/j.neucom.2026.134248_bib0625","series-title":"Computer Vision \u2013 ECCV 2014","first-page":"740","article-title":"Microsoft COCO: common objects in context","author":"Lin","year":"2014"},{"key":"10.1016\/j.neucom.2026.134248_bib0630","doi-asserted-by":"crossref","first-page":"303","DOI":"10.1007\/s11263-009-0275-4","article-title":"The pascal visual object classes (VOC) challenge","volume":"88","author":"Everingham","year":"2010","journal-title":"Int. J. Comput. Vision"},{"key":"10.1016\/j.neucom.2026.134248_bib0635","doi-asserted-by":"crossref","unstructured":"A. Gupta, P. Doll\u00e1r, R. Girshick, LVIS: a dataset for large vocabulary instance segmentation, 2019, https:\/\/arxiv.org\/abs\/1908.03195","DOI":"10.1109\/CVPR.2019.00550"},{"key":"10.1016\/j.neucom.2026.134248_bib0640","series-title":"2019 IEEE\/CVF International Conference on Computer Vision (ICCV)","first-page":"8429","article-title":"Objects365: a large-scale, high-quality dataset for object detection","author":"Shao","year":"2019"},{"key":"10.1016\/j.neucom.2026.134248_bib0645","series-title":"2020 IEEE Winter Conference on Applications of Computer Vision (WACV)","first-page":"1010","article-title":"The overlooked elephant of object detection: open set","author":"Dhamija","year":"2020"},{"key":"10.1016\/j.neucom.2026.134248_bib0650","doi-asserted-by":"crossref","first-page":"170","DOI":"10.1016\/j.patrec.2024.10.002","article-title":"DDOWOD: DiffusionDet for open-world object detection","volume":"186","author":"Fan","year":"2024","journal-title":"Pattern Recognit. Lett."},{"key":"10.1016\/j.neucom.2026.134248_bib0655","doi-asserted-by":"crossref","unstructured":"M. Maaz, H. Rasheed, S. Khan, F.S. Khan, R.M. Anwer, M.-H. Yang, Class-agnostic object detection with multi-modal transformer, 2022, https:\/\/arxiv.org\/abs\/2111.11430","DOI":"10.1007\/978-3-031-20080-9_30"},{"key":"10.1016\/j.neucom.2026.134248_bib0660","doi-asserted-by":"crossref","unstructured":"B.A. Plummer, L. Wang, C.M. Cervantes, J.C. Caicedo, J. Hockenmaier, S. Lazebnik, Flickr30k entities: collecting region-to-phrase correspondences for richer image-to-sentence models, 2016, https:\/\/arxiv.org\/abs\/1505.04870","DOI":"10.1007\/s11263-016-0965-7"},{"key":"10.1016\/j.neucom.2026.134248_bib0665","unstructured":"R. Krishna, Y. Zhu, O. Groth, J. Johnson, K. Hata, J. Kravitz, S. Chen, Y. Kalantidis, L.-J. Li, D.A. Shamma, M.S. Bernstein, F.-F. Li, Visual genome: connecting language and vision using crowdsourced dense image annotations, 2016, https:\/\/arxiv.org\/abs\/1602.07332"},{"key":"10.1016\/j.neucom.2026.134248_bib0670","doi-asserted-by":"crossref","unstructured":"H. Caesar, V. Bankiti, A.H. Lang, S. Vora, V.E. Liong, Q. Xu, A. Krishnan, Y. Pan, G. Baldan, O. Beijbom, nuScenes: a multimodal dataset for autonomous driving, 2020, https:\/\/arxiv.org\/abs\/1903.11027","DOI":"10.1109\/CVPR42600.2020.01164"},{"key":"10.1016\/j.neucom.2026.134248_bib0675","unstructured":"F. Wei, Y. Gao, Z. Wu, H. Hu, S. Lin, Aligning pretraining for detection via object-level contrastive learning, 2021, https:\/\/arxiv.org\/abs\/2106.02637"},{"key":"10.1016\/j.neucom.2026.134248_bib0680","doi-asserted-by":"crossref","unstructured":"A. Kamath, M. Singh, Y. LeCun, G. Synnaeve, I. Misra, N. Carion, MDETR \u2013 modulated detection for end-to-end multi-modal understanding, 2021, https:\/\/arxiv.org\/abs\/2104.12763","DOI":"10.1109\/ICCV48922.2021.00180"},{"key":"10.1016\/j.neucom.2026.134248_bib0685","doi-asserted-by":"crossref","unstructured":"Z. Xia, J. Li, Z. Lin, X. Wang, Y. Wang, M.-H. Yang, OpenAD: open-world autonomous driving benchmark for 3D object detection, 2025, https:\/\/arxiv.org\/abs\/2411.17761","DOI":"10.32388\/J2781I"}],"container-title":["Neurocomputing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0925231226016462?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0925231226016462?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,7,4]],"date-time":"2026-07-04T19:14:54Z","timestamp":1783192494000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0925231226016462"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,10]]},"references-count":137,"alternative-id":["S0925231226016462"],"URL":"https:\/\/doi.org\/10.1016\/j.neucom.2026.134248","relation":{},"ISSN":["0925-2312"],"issn-type":[{"value":"0925-2312","type":"print"}],"subject":[],"published":{"date-parts":[[2026,10]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"From closed sets to dynamic worlds: A comprehensive survey of open world object detection","name":"articletitle","label":"Article Title"},{"value":"Neurocomputing","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.neucom.2026.134248","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"134248"}}