{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,13]],"date-time":"2026-09-13T17:04:01Z","timestamp":1789319041413,"version":"build-2803163510"},"publisher-location":"Cham","reference-count":87,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032375919","type":"print"},{"value":"9783032375926","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\/978-3-032-37592-6_36","type":"book-chapter","created":{"date-parts":[[2026,9,13]],"date-time":"2026-09-13T16:47:27Z","timestamp":1789318047000},"page":"631-654","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["InclusiveHuman-10K: Towards Inclusive Human Parsing Beyond the\u00a0Intact-Limb Assumption"],"prefix":"10.1007","author":[{"given":"Heming","family":"Du","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiaying","family":"Ying","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaofeng","family":"Cao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhu","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuanyuan","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kaihao","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xin","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xin","family":"Yu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,9,14]]},"reference":[{"key":"36_CR1","unstructured":"Clinical commissioning policy: Multi-grip upper limb prosthetics. Tech. Rep. 03736, NHS England (2018). https:\/\/www.england.nhs.uk\/wp-content\/uploads\/2018\/07\/Multi-grip-upper-limb-prosthetics.pdf"},{"key":"36_CR2","unstructured":"Amputee Coalition: Prosthetic feet (2016). https:\/\/amputee-coalition.org\/resources\/prosthetic-feet\/, fact Sheet, Updated Aug 2016"},{"key":"36_CR3","doi-asserted-by":"crossref","unstructured":"An, Z., et al.: Fredn: Spectral disentanglement for time series forecasting via learnable frequency decomposition. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol.\u00a040, pp. 19623\u201319631 (2026)","DOI":"10.1609\/aaai.v40i24.39042"},{"key":"36_CR4","doi-asserted-by":"publisher","unstructured":"Beck, O.N., Taboga, P., Grabowski, A.M.: Characterizing the mechanical properties of running-specific prostheses. PLOS ONE 11(12), e0168298 (2016). https:\/\/doi.org\/10.1371\/journal.pone.0168298, https:\/\/journals.plos.org\/plosone\/article?id=10.1371\/journal.pone.0168298","DOI":"10.1371\/journal.pone.0168298"},{"key":"36_CR5","doi-asserted-by":"publisher","unstructured":"Caesar, H., Uijlings, J.R.R., Ferrari, V.: Coco-stuff: Thing and stuff classes in context. In: 2018 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2018, Salt Lake City, UT, USA, June 18-22, 2018, pp. 1209\u20131218. Computer Vision Foundation \/ IEEE Computer Society (2018). https:\/\/doi.org\/10.1109\/CVPR.2018.00132, http:\/\/openaccess.thecvf.com\/content_cvpr_2018\/html\/Caesar_COCO-Stuff_Thing_and_CVPR_2018_paper.html","DOI":"10.1109\/CVPR.2018.00132"},{"key":"36_CR6","doi-asserted-by":"publisher","unstructured":"Cao, X., et al.: Analytical survey of learning with low-resource data: From analysis to investigation. ACM Comput. Surv. 58(6), 144:1\u2013144:47 (2026). https:\/\/doi.org\/10.1145\/3773075","DOI":"10.1145\/3773075"},{"key":"36_CR7","doi-asserted-by":"publisher","unstructured":"Chen, L., Papandreou, G., Kokkinos, I., Murphy, K., Yuille, A.L.: Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs. IEEE Trans. Pattern Anal. Mach. Intell. 40(4), 834\u2013848 (2018). https:\/\/doi.org\/10.1109\/TPAMI.2017.2699184","DOI":"10.1109\/TPAMI.2017.2699184"},{"key":"36_CR8","doi-asserted-by":"publisher","unstructured":"Chen, X., Mottaghi, R., Liu, X., Fidler, S., Urtasun, R., Yuille, A.L.: Detect what you can: Detecting and representing objects using holistic models and body parts. In: 2014 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2014, Columbus, OH, USA, June 23-28, 2014, pp. 1979\u20131986. IEEE Computer Society (2014). https:\/\/doi.org\/10.1109\/CVPR.2014.254","DOI":"10.1109\/CVPR.2014.254"},{"key":"36_CR9","doi-asserted-by":"publisher","unstructured":"Cheng, B., Girshick, R.B., Doll\u00e1r, P., Berg, A.C., Kirillov, A.: Boundary iou: Improving object-centric image segmentation evaluation. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2021, virtual, June 19-25, 2021, pp. 15334\u201315342. Computer Vision Foundation \/ IEEE (2021). https:\/\/doi.org\/10.1109\/CVPR46437.2021.01508, https:\/\/openaccess.thecvf.com\/content\/CVPR2021\/html\/Cheng_Boundary_IoU_Improving_Object-Centric_Image_Segmentation_Evaluation_CVPR_2021_paper.html","DOI":"10.1109\/CVPR46437.2021.01508"},{"key":"36_CR10","doi-asserted-by":"publisher","unstructured":"Cheng, B., Misra, I., Schwing, A.G., Kirillov, A., Girdhar, R.: Masked-attention mask transformer for universal image segmentation. In: IEEE\/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2022, New Orleans, LA, USA, June 18-24, 2022, pp. 1280\u20131289. IEEE (2022). https:\/\/doi.org\/10.1109\/CVPR52688.2022.00135","DOI":"10.1109\/CVPR52688.2022.00135"},{"key":"36_CR11","unstructured":"Cheng, B., Schwing, A.G., Kirillov, A.: Per-pixel classification is not all you need for semantic segmentation. In: Ranzato, M., Beygelzimer, A., Dauphin, Y.N., Liang, P., Vaughan, J.W. (eds.) Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual, pp. 17864\u201317875 (2021). https:\/\/proceedings.neurips.cc\/paper\/2021\/hash\/950a4152c2b4aa3ad78bdd6b366cc179-Abstract.html"},{"key":"36_CR12","doi-asserted-by":"publisher","first-page":"5159","DOI":"10.1109\/TIP.2024.3456004","volume":"33","author":"J Chu","year":"2024","unstructured":"Chu, J., et al.: Uniparser: multi-human parsing with unified correlation representation learning. IEEE Trans. Image Process. 33, 5159\u20135171 (2024)","journal-title":"IEEE Trans. Image Process."},{"key":"36_CR13","doi-asserted-by":"publisher","unstructured":"Deng, W., et al.: Pos3r: 6d pose estimation for unseen objects made easy. In: IEEE\/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2025, Nashville, TN, USA, June 11-15, 2025, pp. 16818\u201316828. Computer Vision Foundation \/ IEEE (2025). https:\/\/doi.org\/10.1109\/CVPR52734.2025.01567, https:\/\/openaccess.thecvf.com\/content\/CVPR2025\/html\/Deng_Pos3R_6D_Pose_Estimation_for_Unseen_Objects_Made_Easy_CVPR_2025_paper.html","DOI":"10.1109\/CVPR52734.2025.01567"},{"key":"36_CR14","doi-asserted-by":"publisher","unstructured":"Du, H., Du, S., Li, W.: Probabilistic time series forecasting with deep non-linear state space models. CAAI Trans. Intell. Technol. 8(1), 3\u201313 (2023). https:\/\/doi.org\/10.1049\/CIT2.12085","DOI":"10.1049\/CIT2.12085"},{"key":"36_CR15","doi-asserted-by":"publisher","unstructured":"Du, H., Li, L., Huang, Z., Yu, X.: Object-goal visual navigation via effective exploration of relations among historical navigation states. In: IEEE\/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2023, Vancouver, BC, Canada, June 17-24, 2023, pp. 2563\u20132573. IEEE (2023). https:\/\/doi.org\/10.1109\/CVPR52729.2023.00252","DOI":"10.1109\/CVPR52729.2023.00252"},{"key":"36_CR16","doi-asserted-by":"crossref","unstructured":"Du, H., Ying, J., Chen, X., Wang, S., Li, X., Yu, X.: Same person, different depiction: Counterfactual evaluation of vision-language models on individuals with limb deficiencies. In: European Conference on Computer Vision (ECCV) (2026)","DOI":"10.1007\/978-3-032-36969-7_37"},{"key":"36_CR17","unstructured":"Du, H., Ying, J., Wang, S., Li, X., Zhang, K., Yu, X.: Inclusivevidpose: Bridging the pose estimation gap for individuals with limb deficiencies in video-based motion. In: The Fourteenth International Conference on Learning Representations (2026). https:\/\/openreview.net\/forum?id=SyQqXAdWUq"},{"key":"36_CR18","unstructured":"Du, H., Ying, J., Zhang, K., Zhu, T., Yu, X.: Position: Human-centric vision requires topological generalization beyond fixed skeletal topologies. In: Forty-third International Conference on Machine Learning Position Paper Track (2026). https:\/\/openreview.net\/forum?id=2N3dVx1soP"},{"key":"36_CR19","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1007\/978-3-030-58571-6_2","volume-title":"Computer Vision \u2013 ECCV 2020","author":"H Du","year":"2020","unstructured":"Du, H., Yu, X., Zheng, L.: Learning Object Relation Graph and Tentative Policy for Visual Navigation. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.-M. (eds.) ECCV 2020. LNCS, vol. 12352, pp. 19\u201334. Springer (2020). https:\/\/doi.org\/10.1007\/978-3-030-58571-6_2"},{"key":"36_CR20","unstructured":"Du, H., Yu, X., Zheng, L.: Vtnet: Visual transformer network for object goal navigation. In: 9th International Conference on Learning Representations, ICLR 2021, Virtual Event, Austria, May 3-7, 2021. OpenReview.net (2021). https:\/\/openreview.net\/forum?id=DILxQP08O3B"},{"issue":"2","key":"36_CR21","doi-asserted-by":"publisher","first-page":"1840","DOI":"10.1109\/LRA.2024.3523231","volume":"10","author":"X Du","year":"2024","unstructured":"Du, X., Sun, H., Lu, M., Zhu, T., Yu, X.: Dreamcar: Leveraging car-specific prior for in-the-wild 3d car reconstruction. IEEE Robot. Autom. Lett. 10(2), 1840\u20131847 (2024)","journal-title":"IEEE Robot. Autom. Lett."},{"key":"36_CR22","doi-asserted-by":"crossref","unstructured":"Du, X., et\u00a0al.: 3drealcar: An in-the-wild rgb-d car dataset with 360-degree views. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 26488\u201326498 (2025)","DOI":"10.1109\/ICCV51701.2025.02458"},{"key":"36_CR23","doi-asserted-by":"crossref","unstructured":"Du, X., Wang, Y., Yu, X.: Mvgs: Multi-view regulated gaussian splatting for novel view synthesis (2026). https:\/\/arxiv.org\/abs\/2410.02103","DOI":"10.1007\/978-3-032-37232-1_31"},{"key":"36_CR24","unstructured":"Du, X., Wang, Y., Zhan, K., Yu, X.: Mobile-gs: Real-time gaussian splatting for mobile devices. arXiv preprint arXiv:2603.11531 (2026)"},{"key":"36_CR25","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2024.128129","volume":"600","author":"X Du","year":"2024","unstructured":"Du, X., Yu, X., Liu, J., Dai, B., Xu, F.: Ethics-aware face recognition aided by synthetic face images. Neurocomputing 600, 128129 (2024)","journal-title":"Neurocomputing"},{"key":"36_CR26","doi-asserted-by":"publisher","unstructured":"Feng, X., Du, H., Fan, H., Duan, Y., Liu, Y.: Seformer: Structure embedding transformer for 3d object detection. In: Williams, B., Chen, Y., Neville, J. (eds.) Thirty-Seventh AAAI Conference on Artificial Intelligence, AAAI 2023, Thirty-Fifth Conference on Innovative Applications of Artificial Intelligence, IAAI 2023, Thirteenth Symposium on Educational Advances in Artificial Intelligence, EAAI 2023, Washington, DC, USA, February 7-14, 2023. pp. 632\u2013640. AAAI Press (2023). https:\/\/doi.org\/10.1609\/AAAI.V37I1.25139","DOI":"10.1609\/AAAI.V37I1.25139"},{"key":"36_CR27","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"805","DOI":"10.1007\/978-3-030-01225-0_47","volume-title":"Computer Vision \u2013 ECCV 2018","author":"K Gong","year":"2018","unstructured":"Gong, K., Liang, X., Li, Y., Chen, Y., Yang, M., Lin, L.: Instance-Level Human Parsing via Part Grouping Network. In: Ferrari, V., Hebert, M., Sminchisescu, C., Weiss, Y. (eds.) ECCV 2018. LNCS, vol. 11208, pp. 805\u2013822. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-01225-0_47"},{"key":"36_CR28","doi-asserted-by":"publisher","unstructured":"Gong, K., Liang, X., Zhang, D., Shen, X., Lin, L.: Look into person: Self-supervised structure-sensitive learning and a new benchmark for human parsing. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017, Honolulu, HI, USA, July 21-26, 2017, pp. 6757\u20136765. IEEE Computer Society (2017). https:\/\/doi.org\/10.1109\/CVPR.2017.715","DOI":"10.1109\/CVPR.2017.715"},{"key":"36_CR29","unstructured":"Guo, M., Lu, C., Hou, Q., Liu, Z., Cheng, M., Hu, S.: Segnext: Rethinking convolutional attention design for semantic segmentation. In: Koyejo, S., Mohamed, S., Agarwal, A., Belgrave, D., Cho, K., Oh, A. (eds.) Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, NeurIPS 2022, New Orleans, LA, USA, November 28 - December 9, 2022 (2022). http:\/\/papers.nips.cc\/paper_files\/paper\/2022\/hash\/08050f40fff41616ccfc3080e60a301a-Abstract-Conference.html"},{"key":"36_CR30","doi-asserted-by":"publisher","unstructured":"Gupta, A., Doll\u00e1r, P., Girshick, R.B.: LVIS: A dataset for large vocabulary instance segmentation. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2019, Long Beach, CA, USA, June 16-20, 2019, pp. 5356\u20135364. Computer Vision Foundation \/ IEEE (2019). https:\/\/doi.org\/10.1109\/CVPR.2019.00550, http:\/\/openaccess.thecvf.com\/content_CVPR_2019\/html\/Gupta_LVIS_A_Dataset_for_Large_Vocabulary_Instance_Segmentation_CVPR_2019_paper.html","DOI":"10.1109\/CVPR.2019.00550"},{"key":"36_CR31","doi-asserted-by":"publisher","unstructured":"Gustafson, L., et al.: FACET: fairness in computer vision evaluation benchmark. In: IEEE\/CVF International Conference on Computer Vision, ICCV 2023, Paris, France, October 1-6, 2023, pp. 20313\u201320325. IEEE (2023). https:\/\/doi.org\/10.1109\/ICCV51070.2023.01863","DOI":"10.1109\/ICCV51070.2023.01863"},{"key":"36_CR32","doi-asserted-by":"publisher","unstructured":"He, K., Gkioxari, G., Doll\u00e1r, P., Girshick, R.B.: Mask R-CNN. In: IEEE International Conference on Computer Vision, ICCV 2017, Venice, Italy, October 22-29, 2017, pp. 2980\u20132988. IEEE Computer Society (2017). https:\/\/doi.org\/10.1109\/ICCV.2017.322","DOI":"10.1109\/ICCV.2017.322"},{"issue":"1","key":"36_CR33","doi-asserted-by":"publisher","first-page":"150","DOI":"10.1038\/s41597-020-0494-7","volume":"7","author":"S Hood","year":"2020","unstructured":"Hood, S., Ishmael, M.K., Gunnell, A., Foreman, K., Lenzi, T.: A kinematic and kinetic dataset of 18 above-knee amputees walking at various speeds. Sci. Data 7(1), 150 (2020)","journal-title":"Sci. Data"},{"key":"36_CR34","doi-asserted-by":"publisher","unstructured":"Hou, Y., Gould, S., Zheng, L.: Learning to select views for efficient multi-view understanding. In: IEEE\/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2024, Seattle, WA, USA, June 16-22, 2024, pp. 20135\u201320144. IEEE (2024). https:\/\/doi.org\/10.1109\/CVPR52733.2024.01903","DOI":"10.1109\/CVPR52733.2024.01903"},{"key":"36_CR35","doi-asserted-by":"publisher","unstructured":"Hou, Y., Gould, S., Zheng, L.: Scalable deep color quantization: A cluster imitation approach. IEEE Trans. Image Process. 33, 5273\u20135283 (2024). https:\/\/doi.org\/10.1109\/TIP.2024.3414132","DOI":"10.1109\/TIP.2024.3414132"},{"key":"36_CR36","doi-asserted-by":"publisher","unstructured":"Hou, Y., Zheng, L., Torr, P.: Learning camera movement control from real-world drone videos. CoRR abs\/2412.09620 (2024). https:\/\/doi.org\/10.48550\/ARXIV.2412.09620","DOI":"10.48550\/ARXIV.2412.09620"},{"key":"36_CR37","doi-asserted-by":"publisher","unstructured":"Hu, X., Lin, Y., Wang, S., Wu, Z., Lv, K.: Agent-centric relation graph for object visual navigation. IEEE Trans. Circuits Syst. Video Technol. 34(2), 1295\u20131309 (2024). https:\/\/doi.org\/10.1109\/TCSVT.2023.3291131","DOI":"10.1109\/TCSVT.2023.3291131"},{"key":"36_CR38","doi-asserted-by":"publisher","unstructured":"Huang, W., Ghahremani, S., Pei, S., Zhang, Y.: Wheelpose: Data synthesis techniques to improve pose estimation performance on wheelchair users. In: Mueller, F.F., et al. (eds.) Proceedings of the CHI Conference on Human Factors in Computing Systems, CHI 2024, Honolulu, HI, USA, May 11-16, 2024, pp. 944:1\u2013944:25. ACM (2024). https:\/\/doi.org\/10.1145\/3613904.3642555","DOI":"10.1145\/3613904.3642555"},{"key":"36_CR39","unstructured":"Khan, M.W., et al.: RVD: A handheld device-based fundus video dataset for retinal vessel segmentation. In: Oh, A., Naumann, T., Globerson, A., Saenko, K., Hardt, M., Levine, S. (eds.) Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023 (2023). http:\/\/papers.nips.cc\/paper_files\/paper\/2023\/hash\/3a71ee306d6991f2f87dd414e0bdf851-Abstract-Datasets_and_Benchmarks.html"},{"key":"36_CR40","doi-asserted-by":"publisher","unstructured":"Kirillov, A., et al.: Segment anything. In: IEEE\/CVF International Conference on Computer Vision, ICCV 2023, Paris, France, October 1-6, 2023, pp. 3992\u20134003. IEEE (2023). https:\/\/doi.org\/10.1109\/ICCV51070.2023.00371","DOI":"10.1109\/ICCV51070.2023.00371"},{"key":"36_CR41","unstructured":"Leeds Teaching Hospitals NHS Trust: Multi-grip prosthetic hands & digit (2025). https:\/\/www.leedsth.nhs.uk\/patients\/resources\/multi-grip-prosthetic-hands-digit\/, leaflet LN005838. Last Reviewed 04 June 2025"},{"key":"36_CR42","doi-asserted-by":"crossref","unstructured":"Li, J., et al.: Lgfnet: Local correlation and global context fusion for multivariate time series forecasting. In: ICASSP 2026-2026 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 2231\u20132235. IEEE (2026)","DOI":"10.1109\/ICASSP55912.2026.11462340"},{"key":"36_CR43","doi-asserted-by":"crossref","unstructured":"Li, J., et al.: Cadmamba: Clustering adaptive mamba for multivariate time series forecasting. In: ICASSP 2026-2026 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 3066\u20133070 IEEE (2026)","DOI":"10.1109\/ICASSP55912.2026.11464113"},{"key":"36_CR44","doi-asserted-by":"crossref","unstructured":"Li, J., et al.: Pamnet: Patch-adaptive mixing network for multivariate time series forecasting. In: ICASSP 2026-2026 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 5836\u20135840. IEEE (2026)","DOI":"10.1109\/ICASSP55912.2026.11464681"},{"key":"36_CR45","doi-asserted-by":"publisher","unstructured":"Li, P., Xu, Y., Wei, Y., Yang, Y.: Self-correction for human parsing. IEEE Trans. Pattern Anal. Mach. Intell. 44(6), 3260\u20133271 (2022). https:\/\/doi.org\/10.1109\/TPAMI.2020.3048039","DOI":"10.1109\/TPAMI.2020.3048039"},{"key":"36_CR46","doi-asserted-by":"publisher","unstructured":"Li, Y., Mollyn, V., Yuan, K., Carrington, P.: Wheelposer: Sparse-imu based body pose estimation for wheelchair users. In: Flatla, D.R., Hwang, F., Guerreiro, T.J.V., Brewer, R. (eds.) The 26th International ACM SIGACCESS Conference on Computers and Accessibility, ASSETS 2024, St. John\u2019s, NL, Canada, October 27-30, 2024, pp. 8:1\u20138:17. ACM (2024). https:\/\/doi.org\/10.1145\/3663548.3675638","DOI":"10.1145\/3663548.3675638"},{"key":"36_CR47","doi-asserted-by":"publisher","unstructured":"Liang, X., et al.: Deep human parsing with active template regression. IEEE Trans. Pattern Anal. Mach. Intell. 37(12), 2402\u20132414 (2015). https:\/\/doi.org\/10.1109\/TPAMI.2015.2408360","DOI":"10.1109\/TPAMI.2015.2408360"},{"key":"36_CR48","doi-asserted-by":"publisher","unstructured":"Long, J., Shelhamer, E., Darrell, T.: Fully convolutional networks for semantic segmentation. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015, Boston, MA, USA, June 7-12, 2015, pp. 3431\u20133440. IEEE Computer Society (2015). https:\/\/doi.org\/10.1109\/CVPR.2015.7298965","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"36_CR49","doi-asserted-by":"publisher","unstructured":"L\u00fcddecke, T., Ecker, A.S.: Image segmentation using text and image prompts. In: IEEE\/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2022, New Orleans, LA, USA, June 18-24, 2022, pp. 7076\u20137086. IEEE (2022). https:\/\/doi.org\/10.1109\/CVPR52688.2022.00695","DOI":"10.1109\/CVPR52688.2022.00695"},{"key":"36_CR50","unstructured":"Luo, B., Guo, J., Yao, Y., Ding, X.: Adversarial style optimization: Enhancing vlm jailbreaks by grpo-based stylistic triggers optimization. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 11\u201319 (2026)"},{"key":"36_CR51","doi-asserted-by":"publisher","unstructured":"Lv, K., Li, Y., Chen, Z., Wang, S., Han, S., Lin, Y.: Infer the whole from a glimpse of a part: Keypoint-based knowledge graph for vehicle re-identification. In: Walsh, T., Shah, J., Kolter, Z. (eds.) Thirty-Ninth AAAI Conference on Artificial Intelligence, Thirty-Seventh Conference on Innovative Applications of Artificial Intelligence, Fifteenth Symposium on Educational Advances in Artificial Intelligence, AAAI 2025, Philadelphia, PA, USA, February 25 - March 4, 2025, pp. 5901\u20135909. AAAI Press (2025). https:\/\/doi.org\/10.1609\/AAAI.V39I6.32630","DOI":"10.1609\/AAAI.V39I6.32630"},{"key":"36_CR52","unstructured":"NIH MedlinePlus Magazine: How a prosthetic ankle improves balance control (2023). https:\/\/magazine.medlineplus.gov\/article\/how-a-prosthetic-ankle-improves-balance-control\/"},{"key":"36_CR53","doi-asserted-by":"publisher","unstructured":"Rahnama, L., Soulis, K., Geil, M.D.: A review of evidence on mechanical properties of running specific prostheses and their relationship with running performance. Front. Rehabili. Sci. 5, 1402114 (2024). https:\/\/doi.org\/10.3389\/fresc.2024.1402114, https:\/\/www.frontiersin.org\/journals\/rehabilitation-sciences\/articles\/10.3389\/fresc.2024.1402114\/full","DOI":"10.3389\/fresc.2024.1402114"},{"key":"36_CR54","unstructured":"Ravi, N., et al.: SAM 2: Segment anything in images and videos. In: The Thirteenth International Conference on Learning Representations, ICLR 2025, Singapore, April 24-28, 2025. OpenReview.net (2025). https:\/\/openreview.net\/forum?id=Ha6RTeWMd0"},{"key":"36_CR55","unstructured":"Ren, T., et al.: Grounded sam: Assembling open-world models for diverse visual tasks (2024)"},{"key":"36_CR56","doi-asserted-by":"publisher","unstructured":"Ruan, T., Liu, T., Huang, Z., Wei, Y., Wei, S., Zhao, Y.: Devil in the details: Towards accurate single and multiple human parsing. In: The Thirty-Third AAAI Conference on Artificial Intelligence, AAAI 2019, The Thirty-First Innovative Applications of Artificial Intelligence Conference, IAAI 2019, The Ninth AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019, Honolulu, Hawaii, USA, January 27 - February 1, 2019, pp. 4814\u20134821. AAAI Press (2019). https:\/\/doi.org\/10.1609\/AAAI.V33I01.33014814","DOI":"10.1609\/AAAI.V33I01.33014814"},{"key":"36_CR57","doi-asserted-by":"publisher","unstructured":"Segura, D., Romero, E., Abarca, V.E., Elias, D.A.: Upper limb prostheses by the level of amputation: A systematic review. Prosthesis 6(2), 277\u2013300 (2024). https:\/\/doi.org\/10.3390\/prosthesis6020022, https:\/\/www.mdpi.com\/2673-1592\/6\/2\/22","DOI":"10.3390\/prosthesis6020022"},{"key":"36_CR58","unstructured":"Sun, X., Gazagnadou, N., Sharma, V., Lyu, L., Li, H., Zheng, L.: Privacy assessment on reconstructed images: Are existing evaluation metrics faithful to human perception? In: Oh, A., Naumann, T., Globerson, A., Saenko, K., Hardt, M., Levine, S. (eds.) Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023 (2023). http:\/\/papers.nips.cc\/paper_files\/paper\/2023\/hash\/2082273791021571c410f41d565d0b45-Abstract-Conference.html"},{"key":"36_CR59","doi-asserted-by":"publisher","unstructured":"Sun, X., Hou, Y., Deng, W., Li, H., Zheng, L.: Ranking models in unlabeled new environments. In: 2021 IEEE\/CVF International Conference on Computer Vision, ICCV 2021, Montreal, QC, Canada, October 10-17, 2021, pp. 11741\u201311751. IEEE (2021). https:\/\/doi.org\/10.1109\/ICCV48922.2021.01155","DOI":"10.1109\/ICCV48922.2021.01155"},{"key":"36_CR60","unstructured":"Sun, X., Leng, X., Wang, Z., Yang, Y., Huang, Z., Zheng, L.: Cifar-10-warehouse: Broad and more realistic testbeds in model generalization analysis. In: The Twelfth International Conference on Learning Representations, ICLR 2024, Vienna, Austria, May 7-11, 2024. OpenReview.net (2024). https:\/\/openreview.net\/forum?id=pw2ssoOTpo"},{"key":"36_CR61","unstructured":"Sun, X., et al.: Do vlms perceive or recall? probing visual perception vs. memory with classic visual illusions. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 25861\u201325870 (2026)"},{"key":"36_CR62","doi-asserted-by":"publisher","unstructured":"Sun, X., Yao, Y., Wang, S., Li, H., Zheng, L.: Alice benchmarks: Connecting real world object re-identification with the synthetic. CoRR abs\/2310.04416 (2023). https:\/\/doi.org\/10.48550\/ARXIV.2310.04416","DOI":"10.48550\/ARXIV.2310.04416"},{"issue":"1","key":"36_CR63","doi-asserted-by":"publisher","first-page":"38","DOI":"10.3390\/math14010038","volume":"14","author":"Y Tang","year":"2025","unstructured":"Tang, Y., Du, H., Du, S., Li, W.: Integrating deep learning into semiparametric network vector autoregressive models. Mathematics 14(1), 38 (2025)","journal-title":"Mathematics"},{"key":"36_CR64","doi-asserted-by":"crossref","unstructured":"Wang, D., Zhang, S.: Contextual instance decoupling for robust multi-person pose estimation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 11060\u201311068 (2022)","DOI":"10.1109\/CVPR52688.2022.01078"},{"key":"36_CR65","doi-asserted-by":"publisher","unstructured":"Wang, J., et al.: Deep high-resolution representation learning for visual recognition. IEEE Trans. Pattern Anal. Mach. Intell. 43(10), 3349\u20133364 (2021). https:\/\/doi.org\/10.1109\/TPAMI.2020.2983686","DOI":"10.1109\/TPAMI.2020.2983686"},{"key":"36_CR66","unstructured":"Wang, J., Lin, Y., Hu, X., Wang, S., Lv, K.: Local motion matters: A deconstruct-recompose paradigm for reinforcement learning pre-training from videos. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 9859\u20139868 (2026)"},{"key":"36_CR67","doi-asserted-by":"publisher","unstructured":"Wang, S., Wu, Z., Hu, X., Lin, Y., Lv, K.: Skill-based hierarchical reinforcement learning for target visual navigation. IEEE Trans. Multim. 25, 8920\u20138932 (2023). https:\/\/doi.org\/10.1109\/TMM.2023.3243618","DOI":"10.1109\/TMM.2023.3243618"},{"key":"36_CR68","doi-asserted-by":"publisher","unstructured":"Wu, H., et al.: Think how your teammates think: Active inference can benefit decentralized execution. In: Koenig, S., Jenkins, C., Taylor, M.E. (eds.) Fortieth AAAI Conference on Artificial Intelligence, Thirty-Eighth Conference on Innovative Applications of Artificial Intelligence, Sixteenth Symposium on Educational Advances in Artificial Intelligence, AAAI 2026, Singapore, January 20-27, 2026, pp. 29749\u201329757. AAAI Press (2026). https:\/\/doi.org\/10.1609\/AAAI.V40I35.40220","DOI":"10.1609\/AAAI.V40I35.40220"},{"key":"36_CR69","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"432","DOI":"10.1007\/978-3-030-01228-1_26","volume-title":"Computer Vision \u2013 ECCV 2018","author":"T Xiao","year":"2018","unstructured":"Xiao, T., Liu, Y., Zhou, B., Jiang, Y., Sun, J.: Unified Perceptual Parsing for Scene Understanding. In: Ferrari, V., Hebert, M., Sminchisescu, C., Weiss, Y. (eds.) ECCV 2018. LNCS, vol. 11209, pp. 432\u2013448. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-01228-1_26"},{"key":"36_CR70","unstructured":"Xie, E., Wang, W., Yu, Z., Anandkumar, A., \u00c1lvarez, J.M., Luo, P.: Segformer: Simple and efficient design for semantic segmentation with transformers. In: Ranzato, M., Beygelzimer, A., Dauphin, Y.N., Liang, P., Vaughan, J.W. (eds.) Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual, pp. 12077\u201312090 (2021). https:\/\/proceedings.neurips.cc\/paper\/2021\/hash\/64f1f27bf1b4ec22924fd0acb550c235-Abstract.html"},{"key":"36_CR71","doi-asserted-by":"publisher","unstructured":"Xu, J., et al.: Groupvit: Semantic segmentation emerges from text supervision. In: IEEE\/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2022, New Orleans, LA, USA, June 18-24, 2022, pp. 18113\u201318123. IEEE (2022). https:\/\/doi.org\/10.1109\/CVPR52688.2022.01760","DOI":"10.1109\/CVPR52688.2022.01760"},{"key":"36_CR72","unstructured":"Yao, C., et al.: Role-level inductive bias for cross-task generalization in multi-agent reinforcement learning. In: Forty-third International Conference on Machine Learning (2026). https:\/\/openreview.net\/forum?id=oz8kFbXdpj"},{"key":"36_CR73","doi-asserted-by":"publisher","unstructured":"Yao, Y., Gedeon, T., Zheng, L.: Large-scale training data search for object re-identification. In: IEEE\/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2023, Vancouver, BC, Canada, June 17-24, 2023, pp. 15568\u201315578. IEEE (2023). https:\/\/doi.org\/10.1109\/CVPR52729.2023.01494","DOI":"10.1109\/CVPR52729.2023.01494"},{"key":"36_CR74","doi-asserted-by":"publisher","unstructured":"Yao, Y., et al.: Thought graph traversal for test-time scaling in chest x-ray vllms. Pattern Recognit. 179, 113639 (2026). https:\/\/doi.org\/10.1016\/J.PATCOG.2026.113639","DOI":"10.1016\/J.PATCOG.2026.113639"},{"key":"36_CR75","doi-asserted-by":"publisher","unstructured":"Yao, Y., Yang, R., Gedeon, T.: Bipartite mode matching for vision training set search from a hierarchical data server. In: Koenig, S., Jenkins, C., Taylor, M.E. (eds.) Fortieth AAAI Conference on Artificial Intelligence, Thirty-Eighth Conference on Innovative Applications of Artificial Intelligence, Sixteenth Symposium on Educational Advances in Artificial Intelligence, AAAI 2026, Singapore, January 20-27, 2026, pp. 16128\u201316136. AAAI Press (2026). https:\/\/doi.org\/10.1609\/AAAI.V40I19.38648","DOI":"10.1609\/AAAI.V40I19.38648"},{"key":"36_CR76","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"775","DOI":"10.1007\/978-3-030-58539-6_46","volume-title":"Computer Vision \u2013 ECCV 2020","author":"Y Yao","year":"2020","unstructured":"Yao, Y., Zheng, L., Yang, X., Naphade, M., Gedeon, T.: Simulating Content Consistent Vehicle Datasets with Attribute Descent. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.-M. (eds.) ECCV 2020. LNCS, vol. 12351, pp. 775\u2013791. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-58539-6_46"},{"key":"36_CR77","doi-asserted-by":"publisher","unstructured":"Yao, Y., Zheng, L., Yang, X., Napthade, M., Gedeon, T.: Attribute descent: Simulating object-centric datasets on the content level and beyond. IEEE Trans. Pattern Anal. Mach. Intell. 46(4), 2489\u20132505 (2024). https:\/\/doi.org\/10.1109\/TPAMI.2023.3338291","DOI":"10.1109\/TPAMI.2023.3338291"},{"key":"36_CR78","doi-asserted-by":"publisher","unstructured":"Yin, X., et al.: Progait: A multi-purpose video dataset and benchmark for transfemoral prosthesis users. CoRR abs\/2507.10223 (2025). https:\/\/doi.org\/10.48550\/ARXIV.2507.10223","DOI":"10.48550\/ARXIV.2507.10223"},{"key":"36_CR79","unstructured":"Ying, J., Du, H., Zhang, K., Li, L., Yu, X.: Ldpose: Towards inclusive human pose estimation for limb-deficient individuals in the wild"},{"key":"36_CR80","unstructured":"Ying, J., Du, H., Zhang, K., Tweedy, S.M., Yu, X.: Resihmr: Residual-limb aware single-image 3d human mesh recovery for individuals with limb loss. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 13940\u201313950 (2026)"},{"key":"36_CR81","doi-asserted-by":"publisher","first-page":"5599","DOI":"10.1109\/TIP.2022.3192989","volume":"31","author":"S Zhang","year":"2022","unstructured":"Zhang, S., Cao, X., Qi, G.J., Song, Z., Zhou, J.: Aiparsing: Anchor-free instance-level human parsing. IEEE Trans. Image Process. 31, 5599\u20135612 (2022)","journal-title":"IEEE Trans. Image Process."},{"key":"36_CR82","doi-asserted-by":"publisher","unstructured":"Zhao, H., Shi, J., Qi, X., Wang, X., Jia, J.: Pyramid scene parsing network. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017, Honolulu, HI, USA, July 21-26, 2017, pp. 6230\u20136239. IEEE Computer Society (2017). https:\/\/doi.org\/10.1109\/CVPR.2017.660","DOI":"10.1109\/CVPR.2017.660"},{"key":"36_CR83","doi-asserted-by":"publisher","unstructured":"Zheng, S., et al.: Rethinking semantic segmentation from a sequence-to-sequence perspective with transformers. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2021, virtual, June 19-25, 2021, pp. 6881\u20136890. Computer Vision Foundation \/ IEEE (2021). https:\/\/doi.org\/10.1109\/CVPR46437.2021.00681, https:\/\/openaccess.thecvf.com\/content\/CVPR2021\/html\/Zheng_Rethinking_Semantic_Segmentation_From_a_Sequence-to-Sequence_Perspective_With_Transformers_CVPR_2021_paper.html","DOI":"10.1109\/CVPR46437.2021.00681"},{"key":"36_CR84","doi-asserted-by":"publisher","unstructured":"Zhou, B., Zhao, H., Puig, X., Fidler, S., Barriuso, A., Torralba, A.: Scene parsing through ADE20K dataset. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017, Honolulu, HI, USA, July 21-26, 2017, pp. 5122\u20135130. IEEE Computer Society (2017). https:\/\/doi.org\/10.1109\/CVPR.2017.544","DOI":"10.1109\/CVPR.2017.544"},{"key":"36_CR85","doi-asserted-by":"publisher","unstructured":"Zhou, Q., Liang, X., Gong, K., Lin, L.: Adaptive temporal encoding network for video instance-level human parsing. In: Boll, S., Lee, K.M., Luo, J., Zhu, W., Byun, H., Chen, C.W., Lienhart, R., Mei, T. (eds.) 2018 ACM Multimedia Conference on Multimedia Conference, MM 2018, Seoul, Republic of Korea, October 22-26, 2018, pp. 1527\u20131535. ACM (2018). https:\/\/doi.org\/10.1145\/3240508.3240660","DOI":"10.1145\/3240508.3240660"},{"key":"36_CR86","doi-asserted-by":"publisher","unstructured":"Zou, X., et al.: Generalized decoding for pixel, image, and language. In: IEEE\/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2023, Vancouver, BC, Canada, June 17-24, 2023, pp. 15116\u201315127. IEEE (2023). https:\/\/doi.org\/10.1109\/CVPR52729.2023.01451","DOI":"10.1109\/CVPR52729.2023.01451"},{"key":"36_CR87","unstructured":"Zou, X., et al.: Segment everything everywhere all at once. In: Oh, A., Naumann, T., Globerson, A., Saenko, K., Hardt, M., Levine, S. (eds.) Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023 (2023). http:\/\/papers.nips.cc\/paper_files\/paper\/2023\/hash\/3ef61f7e4afacf9a2c5b71c726172b86-Abstract-Conference.html"}],"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\/978-3-032-37592-6_36","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,13]],"date-time":"2026-09-13T16:47:36Z","timestamp":1789318056000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-37592-6_36"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"ISBN":["9783032375919","9783032375926"],"references-count":87,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-37592-6_36","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":"14 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"}}]}}