Intrinsic Light Field Decomposition and Disparity Estimation with Deep Encoder-Decoder Network

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2018
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European Union (EU): 336978
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LIA - Light Field Imaging and Analysis
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EUSIPCO 2018 : 26th European Signal Processing Conference. Piscataway, NJ: IEEE, 2018, pp. 2165-2169. ISBN 9789082797015
Zusammenfassung

We present an encoder-decoder deep neural network that solves non-Lambertian intrinsic light field decomposition, where we recover all three intrinsic components: albedo, shading, and specularity. We learn a sparse set of features from 3D epipolar volumes and use them in separate decoder pathways to reconstruct intrinsic light fields. While being trained on synthetic data generated with Blender, our model still generalizes to real world examples captured with a Lytro Illum plenoptic camera. The proposed method outperforms state-of-the-art approaches for single images and achieves competitive accuracy with recent modeling methods for light fields.

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Fachgebiet (DDC)
004 Informatik
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Decoding, Estimation, Three-dimensional displays, Convolution, Two dimensional displays, Tensile stress, Cameras
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EUSIPCO 2018 : 26th European Signal Processing Conference, 3. Sept. 2018 - 7. Sept. 2018, Rom, Italy
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ISO 690ALPEROVICH, Anna, Ole JOHANNSEN, Bastian GOLDLÜCKE, 2018. Intrinsic Light Field Decomposition and Disparity Estimation with Deep Encoder-Decoder Network. EUSIPCO 2018 : 26th European Signal Processing Conference. Rom, Italy, 3. Sept. 2018 - 7. Sept. 2018. In: EUSIPCO 2018 : 26th European Signal Processing Conference. Piscataway, NJ: IEEE, 2018, pp. 2165-2169. ISBN 9789082797015
BibTex
@inproceedings{Alperovich2018-09Intri-44782,
  year={2018},
  title={Intrinsic Light Field Decomposition and Disparity Estimation with Deep Encoder-Decoder Network},
  isbn={9789082797015},
  publisher={IEEE},
  address={Piscataway, NJ},
  booktitle={EUSIPCO 2018 :  26th European Signal Processing Conference},
  pages={2165--2169},
  author={Alperovich, Anna and Johannsen, Ole and Goldlücke, Bastian}
}
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