Consensus-driven illuminant estimation with GANs

Marco Buzzelli; Riccardo Riva; Simone Bianco; Raimondo Schettini

doi:10.1117/12.2587589

4 January 2021 Consensus-driven illuminant estimation with GANs

Marco Buzzelli, Riccardo Riva, Simone Bianco, Raimondo Schettini

Proceedings Volume 11605, Thirteenth International Conference on Machine Vision; 1160520 (2021) https://doi.org/10.1117/12.2587589
Event: Thirteenth International Conference on Machine Vision, 2020, Rome, Italy

Abstract

We present a method for illuminant estimation that exploits a generative adversarial network architecture to generate a spatially-varying illuminant map. This map is then transformed by consensus into a global illuminant estimation, in the form of a single RGB triplet. To this end, different consensus strategies are designed and compared in this paper. The best solution won second place in the 2nd International Illumination Estimation Challenge, specifically for the indoor track.

Citation Download Citation

Marco Buzzelli, Riccardo Riva, Simone Bianco, and Raimondo Schettini "Consensus-driven illuminant estimation with GANs", Proc. SPIE 11605, Thirteenth International Conference on Machine Vision, 1160520 (4 January 2021); https://doi.org/10.1117/12.2587589

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