{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,3]],"date-time":"2026-09-03T11:15:21Z","timestamp":1788434121265,"version":"build-2803163510"},"reference-count":65,"publisher":"Springer Science and Business Media LLC","issue":"10","license":[{"start":{"date-parts":[[2026,7,25]],"date-time":"2026-07-25T00:00:00Z","timestamp":1784937600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,7,25]],"date-time":"2026-07-25T00:00:00Z","timestamp":1784937600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2024YFC3308500"],"award-info":[{"award-number":["2024YFC3308500"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Beijing Municipal Natural Science Foundation","award":["L251042"],"award-info":[{"award-number":["L251042"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["62406036"],"award-info":[{"award-number":["62406036"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"The State Key Laboratory of Networking and Switching Technology","award":["NST20250110"],"award-info":[{"award-number":["NST20250110"]}]},{"name":"SMP-Zhipu.AI Large Model Cross-Disciplinary Fund","award":["ZPCG20241029322"],"award-info":[{"award-number":["ZPCG20241029322"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Vis Comput"],"published-print":{"date-parts":[[2026,8]]},"DOI":"10.1007\/s00371-026-04585-w","type":"journal-article","created":{"date-parts":[[2026,7,25]],"date-time":"2026-07-25T09:46:58Z","timestamp":1784972818000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["TSMMR: a mixed Mamba network with cross-drone template fusion and text-guided redetection for robust aerial tracking"],"prefix":"10.1007","volume":"42","author":[{"given":"Xiangqian","family":"Liu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guangwei","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yifan","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bing","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,7,25]]},"reference":[{"issue":"12","key":"4585_CR1","doi-asserted-by":"publisher","first-page":"8987","DOI":"10.1007\/s00371-024-03290-w","volume":"40","author":"Z Chen","year":"2024","unstructured":"Chen, Z., Liu, L., Yu, Z.: Toward robust visual tracking for uav with adaptive spatial-temporal weighted regularization. Vis. Comput. 40(12), 8987\u20139003 (2024)","journal-title":"Vis. Comput."},{"issue":"3","key":"4585_CR2","doi-asserted-by":"publisher","first-page":"2119","DOI":"10.1007\/s00371-023-02908-9","volume":"40","author":"J Wang","year":"2024","unstructured":"Wang, J., Li, S., Li, K., Zhu, Q.: Adaptive cascaded and parallel feature fusion for visual object tracking. Vis. Comput. 40(3), 2119\u20132138 (2024)","journal-title":"Vis. Comput."},{"key":"4585_CR3","doi-asserted-by":"crossref","unstructured":"Jin, Q., Han, Y., Wang, W., Tang, L., Li, J., Deng, C.: An occlusion-aware tracker with local-global features modeling in uav videos. IEEE J. Selected Topics Appl. Earth Observations Remote Sens. (2024)","DOI":"10.1109\/JSTARS.2024.3368035"},{"key":"4585_CR4","doi-asserted-by":"publisher","first-page":"9654","DOI":"10.1109\/JSTARS.2022.3216564","volume":"15","author":"Y Han","year":"2022","unstructured":"Han, Y., Liu, H., Wang, Y., Liu, C.: A comprehensive review for typical applications based upon unmanned aerial vehicle platform. IEEE J. Selected Topics Appl. Earth Observations Remote Sens. 15, 9654\u20139666 (2022)","journal-title":"IEEE J. Selected Topics Appl. Earth Observations Remote Sens."},{"key":"4585_CR5","doi-asserted-by":"crossref","unstructured":"Cheng, C.-C., Qiu, M.-X., Chiang, C.-K., Lai, S.-H.: Rest: A reconfigurable spatial-temporal graph model for multi-camera multi-object tracking. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, 10051\u201310060. (2023)","DOI":"10.1109\/ICCV51070.2023.00922"},{"key":"4585_CR6","doi-asserted-by":"crossref","unstructured":"Teepe, T., Wolters, P., Gilg, J., Herzog, F., Rigoll, G.: Earlybird: Early-fusion for multi-view tracking in the bird\u2019s eye view. In: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision, 102\u2013111. (2024)","DOI":"10.1109\/WACVW60836.2024.00018"},{"key":"4585_CR7","doi-asserted-by":"crossref","unstructured":"Wang, B., Tian, Z., Tang, F., Pan, H., She, W., Liu, W.: Blockchain-empowered asynchronous federated reinforcement learning for iot-based traffic trajectory prediction. IEEE Internet Things J., (2025)","DOI":"10.1109\/JIOT.2025.3538887"},{"key":"4585_CR8","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2025.112699","volume":"170","author":"M Majcher","year":"2025","unstructured":"Majcher, M., Kwolek, B.: Object pose tracking using multimodal knowledge from rgb images and quaternion-based rotation contexts. Appl. Soft Comput. 170, 112699 (2025)","journal-title":"Appl. Soft Comput."},{"issue":"66","key":"4585_CR9","doi-asserted-by":"publisher","first-page":"5954","DOI":"10.1126\/scirobotics.abm5954","volume":"7","author":"X Zhou","year":"2022","unstructured":"Zhou, X., Wen, X., Wang, Z., Gao, Y., Li, H., Wang, Q., Yang, T., Lu, H., Cao, Y., Xu, C., et al.: Swarm of micro flying robots in the wild. Sci. Robot. 7(66), 5954 (2022)","journal-title":"Sci. Robot."},{"issue":"10","key":"4585_CR10","doi-asserted-by":"publisher","first-page":"4058","DOI":"10.1109\/TCSVT.2020.3045747","volume":"31","author":"P Zhu","year":"2020","unstructured":"Zhu, P., Zheng, J., Du, D., Wen, L., Sun, Y., Hu, Q.: Multi-drone-based single object tracking with agent sharing network. IEEE Trans. Circuits Syst. Video Technol. 31(10), 4058\u20134070 (2020)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"4585_CR11","doi-asserted-by":"crossref","unstructured":"Chen, G., Zhu, P., Cao, B., Wang, X., Hu, Q.: Cross-drone transformer network for robust single object tracking. IEEE Trans. Circuits Syst. Video Technol. 33(9), 4552\u20134563 (2023)","DOI":"10.1109\/TCSVT.2023.3281557"},{"key":"4585_CR12","doi-asserted-by":"crossref","unstructured":"Sun, D., Cheng, L., Chen, S., Li, C., Xiao, Y., Luo, B.: Uav-ground visual tracking: a unified dataset and collaborative learning approach. In: IEEE Trans. Circuits Syst. Video Technol., (2023)","DOI":"10.1109\/TCSVT.2023.3316990"},{"key":"4585_CR13","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2024.128821","volume":"614","author":"F Cheng","year":"2025","unstructured":"Cheng, F., Peng, G., Li, J., Zhao, B., Pan, J.-S., Li, H.: A transformer-based network with adaptive spatial prior for visual tracking. Neurocomputing 614, 128821 (2025)","journal-title":"Neurocomputing"},{"key":"4585_CR14","unstructured":"Gu, A., Dao, T.: Mamba: Linear-time sequence modeling with selective state spaces, (2023). arXiv preprint arXiv:2312.00752"},{"key":"4585_CR15","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2024.112203","volume":"300","author":"C Ma","year":"2024","unstructured":"Ma, C., Wang, Z.: Semi-mamba-unet: Pixel-level contrastive and cross-supervised visual mamba-based unet for semi-supervised medical image segmentation. Knowl.-Based Syst. 300, 112203 (2024)","journal-title":"Knowl.-Based Syst."},{"key":"4585_CR16","doi-asserted-by":"crossref","unstructured":"Ge, Y., Chen, Z., Yu, M., Yue, Q., You, R., Zhu, L.: Mambatsr: You only need 90k parameters for traffic sign recognition. Neurocomputing, 128104 (2024)","DOI":"10.1016\/j.neucom.2024.128104"},{"key":"4585_CR17","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2024.102589","volume":"112","author":"K Alkilane","year":"2024","unstructured":"Alkilane, K., He, Y., Lee, D.-H.: Mixmamba: time series modeling with adaptive expertise. Inf. Fusion 112, 102589 (2024)","journal-title":"Inf. Fusion"},{"key":"4585_CR18","doi-asserted-by":"crossref","unstructured":"Liu, C., Chen, K., Chen, B., Zhang, H., Zou, Z., Shi, Z.: Rscama: Remote sensing image change captioning with state space model. IEEE Geosci. Remote Sens. Lett. (2024)","DOI":"10.1109\/LGRS.2024.3404604"},{"issue":"11","key":"4585_CR19","doi-asserted-by":"publisher","first-page":"2362","DOI":"10.1109\/TSMC.2018.2808471","volume":"49","author":"Y Liu","year":"2018","unstructured":"Liu, Y., Wang, Q., Hu, H., He, Y.: A novel real-time moving target tracking and path planning system for a quadrotor uav in unknown unstructured outdoor scenes. IEEE Trans. Syst., Man, Cybernetics: Syst. 49(11), 2362\u20132372 (2018)","journal-title":"IEEE Trans. Syst., Man, Cybernetics: Syst."},{"key":"4585_CR20","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s13638-020-01696-3","volume":"2020","author":"Q He","year":"2020","unstructured":"He, Q., Zhang, W., Chen, W., Xie, G., Yao, Y.: Target tracking algorithm combined part-based and redetection for uav. EURASIP J. Wirel. Commun. Netw. 2020, 1\u201317 (2020)","journal-title":"EURASIP J. Wirel. Commun. Netw."},{"key":"4585_CR21","doi-asserted-by":"crossref","unstructured":"Huang, Z., Fu, C., Li, Y., Lin, F., Lu, P.: Learning aberrance repressed correlation filters for real-time uav tracking. In: Proceedings of the IEEE\/CVF International conference on computer vision, 2891\u20132900 (2019)","DOI":"10.1109\/ICCV.2019.00298"},{"key":"4585_CR22","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2022.108485","volume":"118","author":"J Zhang","year":"2022","unstructured":"Zhang, J., Feng, W., Yuan, T., Wang, J., Sangaiah, A.K.: Scstcf: spatial-channel selection and temporal regularized correlation filters for visual tracking. Appl. Soft Comput. 118, 108485 (2022)","journal-title":"Appl. Soft Comput."},{"key":"4585_CR23","doi-asserted-by":"crossref","unstructured":"Li, Y., Fu, C., Ding, F., Huang, Z., Lu, G.: Autotrack: Towards high-performance visual tracking for uav with automatic spatio-temporal regularization. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, 11923\u201311932. (2020)","DOI":"10.1109\/CVPR42600.2020.01194"},{"key":"4585_CR24","doi-asserted-by":"publisher","first-page":"1230","DOI":"10.1109\/LSP.2021.3086675","volume":"28","author":"C Deng","year":"2021","unstructured":"Deng, C., He, S., Han, Y., Zhao, B.: Learning dynamic spatial-temporal regularization for uav object tracking. IEEE Signal Process. Lett. 28, 1230\u20131234 (2021)","journal-title":"IEEE Signal Process. Lett."},{"key":"4585_CR25","doi-asserted-by":"publisher","first-page":"6","DOI":"10.1109\/LSP.2021.3120943","volume":"29","author":"F Zhang","year":"2021","unstructured":"Zhang, F., Ma, S., Zhang, Y., Qiu, Z.: Perceiving temporal environment for correlation filters in real-time uav tracking. IEEE Signal Process. Lett. 29, 6\u201310 (2021)","journal-title":"IEEE Signal Process. Lett."},{"key":"4585_CR26","doi-asserted-by":"crossref","unstructured":"Bertinetto, L., Valmadre, J., Henriques, J.F., Vedaldi, A., Torr, P.H.: Fully-convolutional siamese networks for object tracking. In: Computer Vision\u2013ECCV 2016 Workshops: Amsterdam, The Netherlands, October 8-10 and 15-16, 2016, Proceedings, Part II 14, 850\u2013865 (2016). Springer","DOI":"10.1007\/978-3-319-48881-3_56"},{"issue":"16","key":"4585_CR27","doi-asserted-by":"publisher","first-page":"13539","DOI":"10.1007\/s00521-022-07181-w","volume":"34","author":"S Yang","year":"2022","unstructured":"Yang, S., Xu, J., Chen, H., Wang, M.: High-performance uavs visual tracking using deep convolutional feature. Neural Comput. Appl. 34(16), 13539\u201313558 (2022)","journal-title":"Neural Comput. Appl."},{"key":"4585_CR28","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2022.109912","volume":"132","author":"H Huang","year":"2023","unstructured":"Huang, H., Liu, G., Zhang, Y., Xiong, R.: Feature distillation siamese networks for object tracking. Appl. Soft Comput. 132, 109912 (2023)","journal-title":"Appl. Soft Comput."},{"key":"4585_CR29","doi-asserted-by":"crossref","unstructured":"Voigtlaender, P., Luiten, J., Torr, P.H., Leibe, B.: Siam r-cnn: Visual tracking by re-detection. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp. 6578\u20136588. (2020)","DOI":"10.1109\/CVPR42600.2020.00661"},{"key":"4585_CR30","doi-asserted-by":"crossref","unstructured":"Cao, Z., Fu, C., Ye, J., Li, B., Li, Y.: Hift: Hierarchical feature transformer for aerial tracking. In: Proceedings of the IEEE\/CVF International conference on computer vision, pp. 15457\u201315466 (2021)","DOI":"10.1109\/ICCV48922.2021.01517"},{"key":"4585_CR31","doi-asserted-by":"crossref","unstructured":"Song, Z., Luo, R., Yu, J., Chen, Y.-P.P., Yang, W.: Compact transformer tracker with correlative masked modeling. In: Proceedings of the AAAI conference on artificial intelligence, 37, 2321\u20132329. (2023)","DOI":"10.1609\/aaai.v37i2.25327"},{"key":"4585_CR32","doi-asserted-by":"publisher","first-page":"16743","DOI":"10.52202\/068431-1218","volume":"35","author":"L Lin","year":"2022","unstructured":"Lin, L., Fan, H., Zhang, Z., Xu, Y., Ling, H.: Swintrack: A simple and strong baseline for transformer tracking. Adv. Neural. Inf. Process. Syst. 35, 16743\u201316754 (2022)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"4585_CR33","doi-asserted-by":"crossref","unstructured":"Yan, B., Peng, H., Fu, J., Wang, D., Lu, H.: Learning spatio-temporal transformer for visual tracking. In: Proceedings of the IEEE\/CVF International conference on computer vision, pp. 10448\u201310457. (2021)","DOI":"10.1109\/ICCV48922.2021.01028"},{"key":"4585_CR34","doi-asserted-by":"crossref","unstructured":"Ye, B., Chang, H., Ma, B., Shan, S., Chen, X.: Joint feature learning and relation modeling for tracking: a one-stream framework. In: European conference on computer vision, 341\u2013357. Springer (2022)","DOI":"10.1007\/978-3-031-20047-2_20"},{"key":"4585_CR35","first-page":"1","volume":"60","author":"C Fu","year":"2021","unstructured":"Fu, C., Cao, Z., Li, Y., Ye, J., Feng, C.: Onboard real-time aerial tracking with efficient siamese anchor proposal network. IEEE Trans. Geosci. Remote Sens. 60, 1\u201313 (2021)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"4585_CR36","doi-asserted-by":"publisher","first-page":"50","DOI":"10.1109\/TMM.2021.3120873","volume":"25","author":"X Lin","year":"2021","unstructured":"Lin, X., Sun, S., Huang, W., Sheng, B., Li, P., Feng, D.D.: Eapt: efficient attention pyramid transformer for image processing. IEEE Trans. Multimedia 25, 50\u201361 (2021)","journal-title":"IEEE Trans. Multimedia"},{"key":"4585_CR37","doi-asserted-by":"crossref","unstructured":"Gopal, G.Y., Amer, M.A.: Separable self and mixed attention transformers for efficient object tracking. In: Proceedings of the IEEE\/CVF winter conference on applications of computer vision, 6708\u20136717. (2024)","DOI":"10.1109\/WACV57701.2024.00657"},{"key":"4585_CR38","doi-asserted-by":"publisher","DOI":"10.1016\/j.sysarc.2022.102675","volume":"130","author":"X Sun","year":"2022","unstructured":"Sun, X., Wang, Q., Xie, F., Quan, Z., Wang, W., Wang, H., Yao, Y., Yang, W., Suzuki, S.: Siamese transformer network: building an autonomous real-time target tracking system for uav. J. Syst. Architect. 130, 102675 (2022)","journal-title":"J. Syst. Architect."},{"key":"4585_CR39","doi-asserted-by":"crossref","unstructured":"Xue, Y., Jin, G., Zhong, B., Shen, T., Tan, L., Xue, C., Zheng, Y.: Fmtrack: Frequency-aware interaction and multi-expert fusion for rgb-t tracking. IEEE Trans. Circuits Syst. Video Technol. (2025)","DOI":"10.1109\/TCSVT.2025.3601598"},{"key":"4585_CR40","doi-asserted-by":"crossref","unstructured":"Xue, Y., Jin, G., Shen, T., Tan, L., Wang, N., Gao, J., Yu, Y., Tian, S.: Target-distractor aware uav tracking via global agent. IEEE Trans. Intell. Transp. Syst., (2025)","DOI":"10.1109\/TITS.2025.3581391"},{"issue":"2","key":"4585_CR41","doi-asserted-by":"publisher","first-page":"111","DOI":"10.1016\/j.vrih.2025.02.001","volume":"7","author":"X Yin","year":"2025","unstructured":"Yin, X., He, J., Cheng, Z.: Efficient and lightweight 3d building reconstruction from drone imagery using sparse line and point clouds. Virtual Reality & Intelligent Hardware 7(2), 111\u2013126 (2025)","journal-title":"Virtual Reality & Intelligent Hardware"},{"issue":"1","key":"4585_CR42","doi-asserted-by":"publisher","first-page":"70015","DOI":"10.1002\/cav.70015","volume":"36","author":"L Cai","year":"2025","unstructured":"Cai, L., Zhou, Z.: Visual expansion and real-time calibration for pan-tilt-zoom cameras assisted by panoramic models. Comput. Anim. Virtual Worlds 36(1), 70015 (2025)","journal-title":"Comput. Anim. Virtual Worlds"},{"key":"4585_CR43","doi-asserted-by":"crossref","unstructured":"Xue, Y., Jin, G., Shen, T., Tan, L., Wang, N., Gao, J., Wang, L.: Consistent representation mining for multi-drone single object tracking. IEEE Trans. Circuits Syst. Video Technol. (2024)","DOI":"10.1109\/TCSVT.2024.3411301"},{"key":"4585_CR44","first-page":"572","volume":"34","author":"A Gu","year":"2021","unstructured":"Gu, A., Johnson, I., Goel, K., Saab, K., Dao, T., Rudra, A., R\u00e9, C.: Combining recurrent, convolutional, and continuous-time models with linear state space layers. Adv. Neural. Inf. Process. Syst. 34, 572\u2013585 (2021)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"4585_CR45","unstructured":"Gu, A., Goel, K., R\u00e9, C.: Efficiently modeling long sequences with structured state spaces, (2021). arXiv preprint arXiv:2111.00396"},{"key":"4585_CR46","unstructured":"Zhu, L., Liao, B., Zhang, Q., Wang, X., Liu, W., Wang, X.: Vision mamba: Efficient visual representation learning with bidirectional state space model. arXiv preprint arXiv:2401.09417 (2024)"},{"key":"4585_CR47","unstructured":"Ma, J., Li, F., Wang, B.: U-mamba: Enhancing long-range dependency for biomedical image segmentation, (2024). arXiv preprint arXiv:2401.04722"},{"key":"4585_CR48","doi-asserted-by":"crossref","unstructured":"Huang, J., Wang, S., Wang, S., Wu, Z., Wang, X., Jiang, B.: Mamba-fetrack: Frame-event tracking via state space model. arXiv preprint arXiv:2404.18174 (2024)","DOI":"10.1007\/978-981-97-8858-3_1"},{"issue":"3","key":"4585_CR49","doi-asserted-by":"publisher","first-page":"70030","DOI":"10.1002\/cav.70030","volume":"36","author":"C Lin","year":"2025","unstructured":"Lin, C., Zou, C., Xu, H.: Scnet: a dual-branch network for strong noisy image denoising based on swin transformer and convnext. Compu. Anim. Virtual Worlds 36(3), 70030 (2025)","journal-title":"Compu. Anim. Virtual Worlds"},{"key":"4585_CR50","doi-asserted-by":"publisher","first-page":"2226","DOI":"10.1109\/TMM.2022.3144890","volume":"25","author":"N Jiang","year":"2022","unstructured":"Jiang, N., Sheng, B., Li, P., Lee, T.-Y.: Photohelper: portrait photographing guidance via deep feature retrieval and fusion. IEEE Trans. Multimedia 25, 2226\u20132238 (2022)","journal-title":"IEEE Trans. Multimedia"},{"key":"4585_CR51","doi-asserted-by":"crossref","unstructured":"Wang, M., Liu, Y., Huang, Z.: Large margin object tracking with circulant feature maps. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 4021\u20134029. (2017)","DOI":"10.1109\/CVPR.2017.510"},{"key":"4585_CR52","unstructured":"Radford, A., Kim, J.W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J.: Learning transferable visual models from natural language supervision. In: International conference on machine learning, pp. 8748\u20138763. (2021) . (PmLR)"},{"key":"4585_CR53","doi-asserted-by":"crossref","unstructured":"Kou, Y., Gao, J., Li, B., Wang, G., Hu, W., Wang, Y., Li, L.: Zoomtrack: target-aware non-uniform resizing for efficient visual tracking. Adv. Neural Inf. Process. Syst. 36 (2024)","DOI":"10.52202\/075280-2217"},{"key":"4585_CR54","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, C., Xie, S., Li, Z., Wang, Z.: Target-aware tracking with long-term context attention. In: Proceedings of the AAAI conference on artificial intelligence, vol. 37, pp. 773\u2013780. (2023)","DOI":"10.1609\/aaai.v37i1.25155"},{"key":"4585_CR55","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2024.111278","volume":"161","author":"X Yang","year":"2025","unstructured":"Yang, X., Zeng, D., Wang, X., Wu, Y., Ye, H., Zhao, Q., Li, S.: Adaptively bypassing vision transformer blocks for efficient visual tracking. Pattern Recogn. 161, 111278 (2025)","journal-title":"Pattern Recogn."},{"key":"4585_CR56","doi-asserted-by":"crossref","unstructured":"Danelljan, M., Bhat, G., Khan, F.S., Felsberg, M.: Atom: Accurate tracking by overlap maximization. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp. 4660\u20134669. (2019)","DOI":"10.1109\/CVPR.2019.00479"},{"key":"4585_CR57","doi-asserted-by":"crossref","unstructured":"Bhat, G., Danelljan, M., Gool, L.V., Timofte, R.: Learning discriminative model prediction for tracking. In: Proceedings of the IEEE\/CVF International conference on computer vision, pp. 6182\u20136191. (2019)","DOI":"10.1109\/ICCV.2019.00628"},{"key":"4585_CR58","doi-asserted-by":"crossref","unstructured":"Mayer, C., Danelljan, M., Bhat, G., Paul, M., Paudel, D.P., Yu, F., Van Gool, L.: Transforming model prediction for tracking. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp. 8731\u20138740. (2022)","DOI":"10.1109\/CVPR52688.2022.00853"},{"issue":"10","key":"4585_CR59","doi-asserted-by":"publisher","first-page":"4058","DOI":"10.1109\/TCSVT.2020.3045747","volume":"31","author":"P Zhu","year":"2020","unstructured":"Zhu, P., Zheng, J., Du, D., Wen, L., Sun, Y., Hu, Q.: Multi-drone-based single object tracking with agent sharing network. IEEE Trans. Circuits Syst. Video Technol. 31(10), 4058\u20134070 (2020)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"4585_CR60","doi-asserted-by":"crossref","unstructured":"Tang, F., Ling, Q.: Ranking-based siamese visual tracking. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp. 8741\u20138750. (2022)","DOI":"10.1109\/CVPR52688.2022.00854"},{"issue":"7","key":"4585_CR61","first-page":"8049","volume":"45","author":"X Dong","year":"2022","unstructured":"Dong, X., Shen, J., Porikli, F., Luo, J., Shao, L.: Adaptive siamese tracking with a compact latent network. IEEE Trans. Pattern Anal. Mach. Intell. 45(7), 8049\u20138062 (2022)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"4585_CR62","doi-asserted-by":"crossref","unstructured":"Shi, L., Zhong, B., Liang, Q., Li, N., Zhang, S., Li, X.: Explicit visual prompts for visual object tracking. In: Proceedings of the AAAI conference on artificial intelligence, vol. 38, pp. 4838\u20134846 (2024)","DOI":"10.1609\/aaai.v38i5.28286"},{"key":"4585_CR63","doi-asserted-by":"crossref","unstructured":"Chen, X., Kang, B., Geng, W., Zhu, J., Liu, Y., Wang, D., Lu, H.: Sutrack: Towards simple and unified single object tracking. In: Proceedings of the AAAI conference on artificial intelligence, vol. 39, pp. 2239\u20132247. (2025)","DOI":"10.1609\/aaai.v39i2.32223"},{"key":"4585_CR64","doi-asserted-by":"crossref","unstructured":"Fan, H., Lin, L., Yang, F., Chu, P., Deng, G., Yu, S., Bai, H., Xu, Y., Liao, C., Ling, H.: Lasot: A high-quality benchmark for large-scale single object tracking. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp. 5374\u20135383 (2019)","DOI":"10.1109\/CVPR.2019.00552"},{"key":"4585_CR65","doi-asserted-by":"crossref","unstructured":"Liu, X., Zhang, G., Wang, B., Zhong, L., Zhou, B.: Dynamic spatiotemporal information interaction for multi-drone single object tracking. IEEE Internet Things J. , (2026)","DOI":"10.1109\/JIOT.2026.3659525"}],"container-title":["The Visual Computer"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00371-026-04585-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00371-026-04585-w","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00371-026-04585-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,3]],"date-time":"2026-09-03T10:24:15Z","timestamp":1788431055000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00371-026-04585-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,25]]},"references-count":65,"journal-issue":{"issue":"10","published-print":{"date-parts":[[2026,8]]}},"alternative-id":["4585"],"URL":"https:\/\/doi.org\/10.1007\/s00371-026-04585-w","relation":{},"ISSN":["0178-2789","1432-2315"],"issn-type":[{"value":"0178-2789","type":"print"},{"value":"1432-2315","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,25]]},"assertion":[{"value":"18 January 2026","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 June 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 July 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare no conflict of interest.","order":1,"name":"Ethics","label":"Conflict of interest","group":{"name":"EthicsHeading","label":"Declarations"}}],"article-number":"434"}}