Joint Sampling and Optimisation for Inverse Rendering
Author:
Affiliation:
1. Max Planck Institute for Informatics, Germany
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3610548.3618244
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4. Aaron Defazio Francis Bach and Simon Lacoste-Julien. 2014. SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives. In Advances in Neural Information Processing Systems Z. Ghahramani M. Welling C. Cortes N. Lawrence and K.Q. Weinberger (Eds.). Vol. 27. Curran Associates Inc.https://proceedings.neurips.cc/paper_files/paper/2014/file/ede7e2b6d13a41ddf9f4bdef84fdc737-Paper.pdf
5. Reconstructing Translucent Objects using Differentiable Rendering
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