Self-Supervised Learning for Multi-View Stereo

Author:

ITO Seiya,KANEKO Naoshi,SUMI Kazuhiko

Publisher

Japan Society for Precision Engineering

Subject

Mechanical Engineering

Reference35 articles.

1. 1) A. Kar, C. Häne and J. Malik: Learning a Multi-View Stereo Machine, Annual Conference on Neural Information Processing Systems (NeurIPS), (2017) 364.

2. 2) M. Ji, J. Gall, H. Zheng, Y. Liu and L. Fang: SurfaceNet: An End-to-End 3D Neural Network for Multiview Stereopsis, IEEE International Conference on Computer Vision (ICCV), (2017) 2326.

3. 3) Y. Furukawa and J. Ponce: Accurate, Dense, and Robust Multiview Stereopsis, IEEE Transactions on Pattern Analysis and Machine Intelligence, 32, 8 (2010) 1362.

4. 4) J. L. Schönberger, E. Zheng, J. Frahm and M. Pollefeys: Pixelwise View Selection for Unstructured Multi-View Stereo, European Conference on Computer Vision (ECCV), (2016) 501.

5. 5) S. Galliani, K. Lasinger and K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion, IEEE International Conference on Computer Vision (ICCV), (2015) 873.

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