CGIntrinsics: Better Intrinsic Image Decomposition Through Physically-Based Rendering-Reference-Cited by-同舟云学术

CGIntrinsics: Better Intrinsic Image Decomposition Through Physically-Based Rendering

Published:2018 Issue: Volume: Page:381-399
ISSN:0302-9743
Container-title:Computer Vision – ECCV 2018
language:
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Author:

Li Zhengqi^ORCID,Snavely Noah^ORCID

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-01219-9_23

Reference45 articles.

1. Janner, M., Wu, J., Kulkarni, T., Yildirim, I., Tenenbaum, J.B.: Self-supervised intrinsic image decomposition. In: Neural Information Processing Systems (2017)

2. Shi, J., Dong, Y., Su, H., Yu, S.X.: Learning non-Lambertian object intrinsics across ShapeNet categories. In: Proceedings Computer Vision and Pattern Recognition (CVPR), pp. 5844–5853 (2017)

3. Chang, A.X., et al.: ShapeNet: an information-rich 3D model repository. arXiv preprint arXiv:1512.03012 (2015)

4. Lecture Notes in Computer Science;DJ Butler,2012

5. Bell, S., Bala, K., Snavely, N.: Intrinsic images in the wild. ACM Trans. Graph. 33(4), 159 (2014)

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