Zhao, H., Lai, R., & Xiang, R. (2020). Efficient and robust shape correspondence via sparsity-enforced quadratic assignment. Proceedings / CVPR, IEEE Computer Society Conference on Computer Vision and Pattern Recognition. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1, 9510–9519. https://doi.org/10.1109/CVPR42600.2020.00953

Zhao, Hongkai, Rongjie Lai, and Rui Xiang. “Efficient and robust shape correspondence via sparsity-enforced quadratic assignment.” Proceedings / CVPR, IEEE Computer Society Conference on Computer Vision and Pattern Recognition. IEEE Computer Society Conference on Computer Vision and Pattern Recognition 1 (2020): 9510–19. https://doi.org/10.1109/CVPR42600.2020.00953.

Zhao H, Lai R, Xiang R. Efficient and robust shape correspondence via sparsity-enforced quadratic assignment. Proceedings / CVPR, IEEE Computer Society Conference on Computer Vision and Pattern Recognition IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2020;1:9510–9.

Zhao, Hongkai, et al. “Efficient and robust shape correspondence via sparsity-enforced quadratic assignment.” Proceedings / CVPR, IEEE Computer Society Conference on Computer Vision and Pattern Recognition. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 1, IEEE, 2020, pp. 9510–19. Manual, doi:10.1109/CVPR42600.2020.00953.

Zhao H, Lai R, Xiang R. Efficient and robust shape correspondence via sparsity-enforced quadratic assignment. Proceedings / CVPR, IEEE Computer Society Conference on Computer Vision and Pattern Recognition IEEE Computer Society Conference on Computer Vision and Pattern Recognition. IEEE; 2020;1:9510–9519.