{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T09:42:08Z","timestamp":1785404528808,"version":"3.56.0"},"reference-count":40,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T00:00:00Z","timestamp":1782950400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100014188","name":"Ministry of Science and ICT, MSIT","doi-asserted-by":"publisher","award":["IITP-2026-RS-2020-II201808"],"award-info":[{"award-number":["IITP-2026-RS-2020-II201808"]}],"id":[{"id":"10.13039\/501100014188","id-type":"DOI","asserted-by":"publisher"}]},{"award":["IITP-2026-RS-2020-II201808"],"award-info":[{"award-number":["IITP-2026-RS-2020-II201808"]}],"id":[{"id":"https:\/\/ror.org\/01wpjm123","id-type":"ROR","asserted-by":"publisher"}]},{"name":"Ministry of Education (MOE) and Daegu Metropolitan City, Republic of Korea","award":["2025-RISE-03-001"],"award-info":[{"award-number":["2025-RISE-03-001"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Soccer-video analysis centers on pitch-plane tracking, but camera-view depth cues such as occlusion and goal-area structure are not fully represented on the field plane. Synthetic benchmarks provide dense supervision unavailable for real broadcasts, but whether adaptation yields predictions that are reproducible across matches and operationally feasible remains unclear. We evaluate a Depth Anything V2 model adapted to SoccerNet-Depth with four components: Unaligned MDE accuracy, scale-and-shift aligned diagnostic, match-to-match reliability, and accuracy\u2013cost trade-off. The model achieves an unaligned validation AbsRel of 0.00372. The aligned diagnostic shows that Base DAv2 retained substantial scene-depth structure, whereas SoccerNet adaptation enabled direct compatibility with the normalized target without per-frame ground-truth fitting. Relative to the VKITTI-fine-tuned reference, the adaptation improved all eight metrics in all 21 validation matches, with paired Wilcoxon tests significant after Bonferroni correction. On the challenge split, it reduced AbsRel by 34.1% versus the official baseline. The higher-resolution configuration improved the validation AbsRel by 5.9%, while the default retained a better accuracy\u2013cost balance. At 401.57 ms per frame, the default is suited to post-match analysis, not live or near-real-time use. The study contributes a benchmark-scoped adaptation case study and protocol for foundation MDE on SoccerNet-Depth.<\/jats:p>","DOI":"10.3390\/s26134192","type":"journal-article","created":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T11:48:32Z","timestamp":1782992912000},"page":"4192","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Adapting a Foundation Monocular Depth Model for Soccer Video: From Synthetic Supervision to Match-Level Reliability"],"prefix":"10.3390","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-7443-254X","authenticated-orcid":false,"given":"Ju-Seong","family":"Do","sequence":"first","affiliation":[{"name":"Department of Artificial Intelligence, Kyungpook National University, 80 Daehak-ro, Buk-gu, Daegu 41566, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0398-831X","authenticated-orcid":false,"given":"Ho-Young","family":"Jung","sequence":"additional","affiliation":[{"name":"Department of Artificial Intelligence, Kyungpook National University, 80 Daehak-ro, Buk-gu, Daegu 41566, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,7,2]]},"reference":[{"key":"ref_1","unstructured":"FIFA (2026, April 29). Semi-Automated Offside Technology to be Used at FIFA World Cup 2022. Available online: https:\/\/inside.fifa.com\/innovation\/world-cup-2022\/semi-automated-offside-technology."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Maglo, A., Orcesi, A., Denize, J., and Pham, Q.C. (2023). Individual Locating of Soccer Players from a Single Moving View. Sensors, 23.","DOI":"10.3390\/s23187938"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Guti\u00e9rrez-P\u00e9rez, M., and Agudo, A. (2025, January 11\u201312). SoccerNet-v3D: Leveraging Sports Broadcast Replays for 3D Scene Understanding. Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops, Nashville, TN, USA.","DOI":"10.1109\/CVPRW67362.2025.00595"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Yang, L., Kang, B., Huang, Z., Zhao, Z., Xu, X., Feng, J., and Zhao, H. (2024, January 10\u201315). Depth Anything V2. Proceedings of the Advances in Neural Information Processing Systems (NeurIPS), Vancouver, BC, Canada.","DOI":"10.52202\/079017-0688"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Leduc, A., Cioppa, A., Giancola, S., Ghanem, B., and Van Droogenbroeck, M. (2024, January 17\u201318). SoccerNet-Depth: A Scalable Dataset for Monocular Depth Estimation in Sports Videos. Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, Seattle, WA, USA.","DOI":"10.1109\/CVPRW63382.2024.00333"},{"key":"ref_6","unstructured":"Eigen, D., Puhrsch, C., and Fergus, R. (2014). Depth Map Prediction from a Single Image using a Multi-Scale Deep Network. NIPS\u201914: Proceedings of the 28th International Conference on Neural Information Processing Systems, MIT Press."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1623","DOI":"10.1109\/TPAMI.2020.3019967","article-title":"Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-Shot Cross-Dataset Transfer","volume":"44","author":"Ranftl","year":"2022","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Ranftl, R., Bochkovskiy, A., and Koltun, V. (2021, January 10\u201317). Vision Transformers for Dense Prediction. Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV), Montreal, QC, Canada.","DOI":"10.1109\/ICCV48922.2021.01196"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Yang, L., Kang, B., Huang, Z., Xu, X., Feng, J., and Zhao, H. (2024, January 16\u201322). Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data. Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, Seattle, WA, USA.","DOI":"10.1109\/CVPR52733.2024.00987"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Chen, S., Guo, H., Zhu, S., Zhang, F., Huang, Z., Feng, J., and Kang, B. (2025, January 10\u201317). Video Depth Anything: Consistent Depth Estimation for Super-Long Videos. Proceedings of the 2025 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Nashville, TN, USA.","DOI":"10.1109\/CVPR52734.2025.02126"},{"key":"ref_11","unstructured":"Bhat, S.F., Birkl, R., Wofk, D., Wonka, P., and M\u00fcller, M. (2023). ZoeDepth: Zero-shot Transfer by Combining Relative and Metric Depth. arXiv."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Yin, W., Zhang, C., Chen, H., Cai, Z., Yu, G., Wang, K., Chen, X., and Shen, C. (2023, January 1\u20136). Metric3D: Towards Zero-shot Metric 3D Prediction from A Single Image. Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV), Paris, France.","DOI":"10.1109\/ICCV51070.2023.00830"},{"key":"ref_13","first-page":"746","article-title":"Indoor Segmentation and Support Inference from RGBD Images","volume":"Volume 7576","author":"Silberman","year":"2012","journal-title":"Proceedings of the Computer Vision\u2014ECCV 2012; Lecture Notes in Computer Science"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Geiger, A., Lenz, P., and Urtasun, R. (2012, January 16\u201321). Are We Ready for Autonomous Driving? The KITTI Vision Benchmark Suite. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Providence, RI, USA.","DOI":"10.1109\/CVPR.2012.6248074"},{"key":"ref_15","unstructured":"Cai, Z., and Metzler, C.A. (2025). Underwater Monocular Metric Depth Estimation: Real-World Benchmarks and Synthetic Fine-Tuning with Vision Foundation Models. arXiv."},{"key":"ref_16","first-page":"71","article-title":"Depth Any Canopy: Leveraging Depth Foundation Models for Canopy Height Estimation","volume":"Volume 15624","author":"Corley","year":"2025","journal-title":"Computer Vision\u2014ECCV 2024 Workshops; Lecture Notes in Computer Science"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1013","DOI":"10.1007\/s11548-024-03083-5","article-title":"Surgical-DINO: Adapter Learning of Foundation Models for Depth Estimation in Endoscopic Surgery","volume":"19","author":"Cui","year":"2024","journal-title":"Int. J. Comput. Assist. Radiol. Surg."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1613\/jair.1.12505","article-title":"Game Plan: What AI can do for Football, and What Football can do for AI","volume":"71","author":"Tuyls","year":"2021","journal-title":"J. Artif. Intell. Res."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Giancola, S., Amine, M., Dghaily, T., and Ghanem, B. (2018, January 18\u201322). SoccerNet: A Scalable Dataset for Action Spotting in Soccer Videos. Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Salt Lake City, UT, USA.","DOI":"10.1109\/CVPRW.2018.00223"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Deli\u00e8ge, A., Cioppa, A., Giancola, S., Seikavandi, M.J., Dueholm, J.V., Nasrollahi, K., Ghanem, B., Moeslund, T.B., and Van Droogenbroeck, M. (2021, January 19\u201325). SoccerNet-v2: A Dataset and Benchmarks for Holistic Understanding of Broadcast Soccer Videos. Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Nashville, TN, USA.","DOI":"10.1109\/CVPRW53098.2021.00508"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Cioppa, A., Giancola, S., Deli\u00e8ge, A., Kang, L., Zhou, X., Cheng, Z., Ghanem, B., and Van Droogenbroeck, M. (2022, January 19\u201320). SoccerNet-Tracking: Multiple Object Tracking Dataset and Benchmark in Soccer Videos. Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops, New Orleans, LA, USA.","DOI":"10.1109\/CVPRW56347.2022.00393"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Somers, V., Joos, V., Cioppa, A., Giancola, S., Ghasemzadeh, S.A., Magera, F., Standaert, B., Mansourian, A.M., Zhou, X., and Kasaei, S. (2024, January 17\u201318). SoccerNet Game State Reconstruction: End-to-End Athlete Tracking and Identification on a Minimap. Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops, Seattle, WA, USA.","DOI":"10.1109\/CVPRW63382.2024.00334"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Magera, F., Hoyoux, T., Barnich, O., and Van Droogenbroeck, M. (2024, January 17\u201318). A Universal Protocol to Benchmark Camera Calibration for Sports. Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, Seattle, WA, USA.","DOI":"10.1109\/CVPRW63382.2024.00338"},{"key":"ref_24","unstructured":"Magera, F., Hoyoux, T., Barnich, O., and Van Droogenbroeck, M. (March, January 26). BroadTrack: Broadcast Camera Tracking for Soccer. Proceedings of the 2025 IEEE\/CVF Winter Conference on Applications of Computer Vision (WACV), Tucson, AZ, USA."},{"key":"ref_25","first-page":"102","article-title":"Playing for Data: Ground Truth from Computer Games","volume":"Volume 9906","author":"Richter","year":"2016","journal-title":"Proceedings of the Computer Vision\u2014ECCV 2016; Lecture Notes in Computer Science"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Rematas, K., Kemelmacher-Shlizerman, I., Curless, B., and Seitz, S.M. (2018, January 18\u201323). Soccer on Your Tabletop. Proceedings of the 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, UT, USA.","DOI":"10.1109\/CVPR.2018.00498"},{"key":"ref_27","unstructured":"Giancola, S., Cioppa, A., Guti\u00e9rrez-P\u00e9rez, M., Held, J., Hinojosa, C., Joos, V., Leduc, A., Magera, F., Sanchez, K., and Somers, V. (2025). SoccerNet 2025 Challenges Results. arXiv."},{"key":"ref_28","unstructured":"Gaspar, V., Cioppa, A., Held, J., Giancola, S., Braham, M., Deli\u00e8ge, A., Ghanem, B., and Van Droogenbroeck, M. (2025, January 11\u201312). An End-to-End Pipeline for Virtual Banner Replacement in Football Broadcasts. Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, Nashville, TN, USA."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Xu, Y., Bretzner, L., Wang, T., and Maki, A. (2025, January 11\u201312). Skor-xG: SKeleton-ORiented Expected Goal Estimation in Soccer. Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, Nashville, TN, USA.","DOI":"10.1109\/CVPRW67362.2025.00594"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"217","DOI":"10.2165\/00007256-199826040-00002","article-title":"Statistical Methods for Assessing Measurement Error (Reliability) in Variables Relevant to Sports Medicine","volume":"26","author":"Atkinson","year":"1998","journal-title":"Sport. Med."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1","DOI":"10.2165\/00007256-200030010-00001","article-title":"Measures of Reliability in Sports Medicine and Science","volume":"30","author":"Hopkins","year":"2000","journal-title":"Sports Med."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Linke, D., Link, D., and Lames, M. (2020). Football-specific validity of TRACAB\u2019s optical video tracking systems. PLoS ONE, 15.","DOI":"10.1371\/journal.pone.0230179"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Crang, Z.L., Johnston, R.D., Mills, K.L., Billingham, J., Robertson, S., Cole, M.H., Weakley, J., Hewitt, A., and Duthie, G.M. (2025). Concurrent validity of computer-vision artificial intelligence player tracking software using broadcast footage. arXiv.","DOI":"10.1177\/22150218261445834"},{"key":"ref_34","unstructured":"Agarwal, R., Schwarzer, M., Castro, P.S., Courville, A., and Bellemare, M.G. (2021, January 6\u201314). Deep Reinforcement Learning at the Edge of the Statistical Precipice. Proceedings of the 35th Conference on Neural Information Processing Systems (NeurIPS 2021), Online."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"6977","DOI":"10.1007\/s10994-024-06585-0","article-title":"Methodology and Evaluation in Sports Analytics: Challenges, Approaches, and Lessons Learned","volume":"113","author":"Davis","year":"2024","journal-title":"Mach. Learn."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Zhang, J., Wu, Y., and Jiang, H. (2025). Survey on Monocular Metric Depth Estimation. Computers, 14.","DOI":"10.3390\/computers14110502"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"21859","DOI":"10.1038\/s41598-025-05462-7","article-title":"Real-time analysis of soccer ball\u2013player interactions using graph convolutional networks for enhanced game insights","volume":"15","author":"Majeed","year":"2025","journal-title":"Sci. Rep."},{"key":"ref_38","unstructured":"Cabon, Y., Murray, N., and Humenberger, M. (2020). Virtual KITTI 2. arXiv."},{"key":"ref_39","unstructured":"Wu, S., Nugent, J., Yang, W., and Deng, J. (2025). Toward A Better Understanding of Monocular Depth Evaluation. arXiv."},{"key":"ref_40","first-page":"1","article-title":"Statistical Comparisons of Classifiers over Multiple Data Sets","volume":"7","year":"2006","journal-title":"J. Mach. Learn. Res."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/26\/13\/4192\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T10:31:31Z","timestamp":1783420291000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/26\/13\/4192"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,2]]},"references-count":40,"journal-issue":{"issue":"13","published-online":{"date-parts":[[2026,7]]}},"alternative-id":["s26134192"],"URL":"https:\/\/doi.org\/10.3390\/s26134192","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,2]]}}}