EDP Sciences logo
Submit your paper
Search
Menu
All issues Volume 15 (2024) Int. J. Metrol. Qual. Eng., 15 (2024) 1 References
Open Access
Issue
Int. J. Metrol. Qual. Eng.
Volume 15, 2024
Article Number 1
Number of page(s) 7
DOI https://doi.org/10.1051/ijmqe/2023015
Published online 23 January 2024
  1. S. Fuhrmann, F. Langguth, M. Goesele, Mve-a multiview reconstruction environment, Eurograph. Workshops Graph. Cult. Herit. 11 – 18 (2014) [Google Scholar]
  2. R.A. Newcombe, S.J. Lovegrove, A.J. Davison, Dtam: Dense tracking and mapping in real-time, IEEE Int. Conf. Comput. Vis. 2320–2327 (2011) [Google Scholar]
  3. Y. Xu, X. Liu, L. Qin, S.-C. Zhu, Multi-view people tracking via hierarchical trajectory composition, AAAI Conf. Artif. Intell. 1, (2017) [Google Scholar]
  4. H. Joo, T. Simon, Y. Sheikh, Total capture: a 3D deformation model for tracking faces, hands, and bodies, Comput. Vis. Pattern Recognit. (CVPR) 8320–8329 (2018) [Google Scholar]
  5. M. Loper, N. Mahmood, J. Romero, G. Pons-Moll, M.J. Black, SMPL: a skinned multi-person linear model, Trans. Graph. (TOG). 34, 1–16 (2015) [CrossRef] [Google Scholar]
  6. G. Pavlakos, V. Choutas, N. Ghorbani, T. Bolkart, A.A.A. Osman, D. Tzionas, M.J. Black, Expressive body capture: 3D hands, face, and body from a single image, Comput. Vis. Pattern Recognit. (CVPR). 10975–10985 (2019) [Google Scholar]
  7. J. Romero, D. Tzionas, M.J. Black, Embodied hands: modeling and capturing hands and bodies together, Trans. Graph. (TOG). 36, 1–17 (2017) [CrossRef] [Google Scholar]
  8. H. Xu, E.G. Bazavan, A. Zanfir, W.T. Freeman, R. Sukthankar, C. Sminchisescu, GHUM & GHUML: generative 3D human shape and articulated pose models, Comput. Vis. Pattern Recognit. (CVPR). 6183–6192 (2020) [Google Scholar]
  9. V. Choutas, L. Muller, C.-H.P. Huang, S. Tang, D. Tzionas, M.J. Black, Accurate 3D body shape regression via linguistic attributes and anthropometric measurements, Comput. Vis. Pattern Recognit . (CVPR). (2022) [Google Scholar]
  10. A. Kanazawa, M.J. Black, D.W. Jacobs, J. Malik, End-to-end recovery of human shape and pose, Comput. Vis. Pattern Recognit. (CVPR). 7122–7131 (2018) [Google Scholar]
  11. M. Kocabas, N. Athanasiou, M.J. Black, VIBE: Video inference for human body pose and shape estimation, Comput. Vis. Pattern Recognit. (CVPR). 5252–5262 (2020) [Google Scholar]
  12. N. Kolotouros, G. Pavlakos, M.J. Black, K. Daniilidis, Learning to reconstruct 3D human pose and shape via model-fitting in the loop, Int. Conf. Comput. Vis. (ICCV). 2252–2261 (2019) [Google Scholar]
  13. D. Smith, M. Loper, X. Hu, P. Mavroidis, J. Romero, FACSIMILE: Fast and accurate scans from an image in less than a second, Int. Conf. Comput. Vis. (ICCV). 5330–5339 (2019) [Google Scholar]
  14. Y. Sun, W. Liu, Q. Bao, Y. Fu, T. Mei, M.J. Black, Putting people in their place: monocular regression of 3D people in depth, Comput. Vis. Pattern Recognit. (CVPR). (2022) [Google Scholar]
  15. H. Yi, C.-H.P. Huang, D. Tzionas, M. Kocabas, M. Hassan, S. Tang, J. Thies, M.J. Black, Human-aware object placement for visual environment reconstruction,Comput. Vis. Pattern Recognit. (CVPR). (2022) [Google Scholar]
  16. T. Alldieck, M.A. Magnor, B.L. Bhatnagar, C. Theobalt, G. Pons-Moll, Learning to reconstruct people in clothing from a single RGB camera, Comput. Vis. Pattern Recognit. (CVPR). 1175–1186 (2019) [Google Scholar]
  17. T. Alldieck, M.A. Magnor, W. Xu, C. Theobalt, G. Pons-Moll, Detailed human avatars from monocular video, Int. Conf. 3D Vis. (3DV). 98–109 (2018) [Google Scholar]
  18. T. Alldieck, M.A. Magnor, W. Xu, C. Theobalt, G. Pons-Moll, Video based reconstruction of 3D people models, Comput. Vis. Pattern Recognit. (CVPR). 8387–8397 (2018) [Google Scholar]
  19. T. Alldieck, G. Pons-Moll, C. Theobalt, M.A. Magnor, Tex2Shape: detailed full human body geometry from a single image, Int. Conf. Comput. Vis. (ICCV). 2293–2303 (2019) [Google Scholar]
  20. V. Lazova, E. Insafutdinov, G. Pons-Moll 360-degree textures of people in clothing from a single image, Int. Conf. 3D Vis. (3DV). 643– 653 (2019) [Google Scholar]
  21. G. Pons-Moll, S. Pujades, S. Hu, M.J. Black, ClothCap: seamless 4D clothing capture and retargeting, Trans. Graph. (TOG). 36, 1–15 (2017) [CrossRef] [Google Scholar]
  22. D. Xiang, F. Prada, C. Wu, J.K. Hodgins, MonoClothCap: towards temporally coherent clothing capture from monocular RGB video, Int. Conf. 3D Vis. (3DV). 322–332 (2020) [Google Scholar]
  23. H. Zhu, X. Zuo, S. Wang, X. Cao, R. Yang, Detailed human shape estimation from a single image by hierarchical mesh deformation, Comput. Vis. Pattern Recognit. (CVPR). 4491–4500 (2019) [Google Scholar]
  24. Z. Chen, H. Zhang, Learning implicit fields for generative shape modelling, Comput. Vis. Pattern Recognit. (CVPR). 5939–5948 (2019) [Google Scholar]
  25. L.M. Mescheder, M. Oechsle, M. Niemeyer, S. Nowozin, A. Geiger, Occupancy networks: learning 3D reconstruction in function space, Comput. Vis. Pattern Recognit. (CVPR). 4460–4470 (2019) [Google Scholar]
  26. J.J. Park, P. Florence, J. Straub, R.A. Newcombe, S. Lovegrove, DeepSDF: learning continuous signed distance functions for shape representation, Comput. Vis. Pattern Recognit. (CVPR). 165–174 (2019) [Google Scholar]
  27. S. Saito, Z. Huang, R. Natsume, S. Morishima, H. Li, A. Kanazawa, PIFu: pixel-aligned implicit function for high-resolution clothed human digitization, Int. Conf. Comput. Vis. (ICCV). 2304–2314 (2019) [Google Scholar]
  28. S. Saito, T. Simon, J.M. Saragih, H. Joo, PIFuHD: multi-level pixel-aligned implicit function for high-resolution 3D human digitization, Comput. Vis. Pattern Recognit. (CVPR). 81–90 (2020) [Google Scholar]
  29. T. He, J.P. Collomosse, H. Jin, S. Soatto, Geo-PIFu: geometry and pixel aligned implicit functions for single-view human reconstruction, Conf. Neural Inf. Process. Syst. (NeurIPS). (2020) [Google Scholar]
  30. Z. Li, T. Yu, C. Pan, Z. Zheng, Y. Liu, Robust 3D self-portraits in Seconds, Comput. Vis. Pattern Recognit. (CVPR). 1341–1350 (2020) [Google Scholar]
  31. Z. Dong, C. Guo, J. Song, X. Chen, A. Geiger, O. Hilliges, PINA: learning a personalized implicit neural avatar from a single RGB-D video sequence, Comput. Vis. Pattern Recognit. (CVPR). (2022) [Google Scholar]
  32. R. Li, K. Olszewski, Y. Xiu, S. Saito, Z. Huang, H. Li, Volumetric human teleportation, ACM SIGGRAPH 2020 Real-Time Live. 1–1 (2020) [Google Scholar]
  33. R. Li, Y. Xiu, S. Saito, Z. Huang, K. Olszewski, H. Li, Monocular real-time volumetric performance capture, Eur. Conf. Comput. Vis. (ECCV). 12368, 49–67 (2020) [Google Scholar]
  34. F. Bogo, A. Kanazawa, C. Lassner, P. Gehler, J. Romero, M.J. Black, Keep it SMPL: automatic estimation of 3D human pose and shape from a single image, Eur. Conf. Comput. Vis. Springer International Publishing. (2016) [Google Scholar]
  35. M. Kocabas, C.-H.P. Huang, O. Hilliges, M.J. Black, PARE: part attention regressor for 3D human body estimation, Int. Conf. Comput. Vis. (ICCV). 11127–11137 (2021) [Google Scholar]
  36. Z. Cao, G.H. Martinez, T. Simon, S.-E. Wei, Y.A. Sheikh, Openpose: realtime multi-person 2d pose estimation using part affinity fields, IEEE Trans. Pattern Anal. Mach. Intell. (2019) [Google Scholar]
  37. M.M. Loper, N. Mahmood, J. Romero, G. Pons-Moll, M.J. Black, SMPL: a skinned multi-person linear model, ACM Trans. Graph. 34, 1–16 (2015) [CrossRef] [Google Scholar]
  38. S. Liu, T. Li, W. Chen, H. Li, Soft rasterizer: a differentiable renderer for image-based 3d reasoning, Proc. IEEE Int. Conf. Comput. Vis. 7708–7717 (2019) [Google Scholar]
  39. O. Sorkine, D. Cohen-Or, Y. Lipman, M. Alexa, C. Rossl, H.P. Seidel, Laplacian surface editing,Eurogr./ACM SIGGRAPH Symp. Geom. Process. 175–184 (2004) [Google Scholar]
  40. https://graphics.tu-bs.de/people-snapshot [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.