PushNet: 3D reconstruction from a single image by pushing
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Link
https://link.springer.com/content/pdf/10.1007/s00521-023-09408-w.pdf
Reference35 articles.
1. Kolev K, Cremers D, (2008) Integration of multiview stereo and silhouettes via convex functionals on convex domains. In: European conference on computer vision, Springer, (pp. 752–765).
2. Kostrikov I, Horbert E, Leibe B, (2014) Probabilistic labeling cost for high-accuracy multi-view reconstruction. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, (pp. 1534–1541)
3. Kar AC, Malik J, (2017) Learning a multi-view stereo machine. arXiv preprint arXiv:1708.05375
4. Wen C, Zhang Y, Li Z, Fu Y, (2019) Pixel2mesh++: multi-view 3d mesh generation via deformation. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, (pp. 1042–1051)
5. Choy CB, Xu D, Gwak J, Chen K, Savarese S, (2016) 3d-r2n2: a unified approach for single and multi-view 3d object reconstruction. In: European conference on computer vision. Springer, (pp. 628–644)
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