GMLight: Lighting Estimation via Geometric Distribution Approximation. (arXiv:2102.10244v2 [cs.CV] UPDATED)

Inferring the scene illumination from a single image is an essential yet
challenging task in computer vision and computer graphics. Existing works
estimate lighting by regressing representative illumination parameters or
generating illumination maps directly. However, these methods often suffer from
poor accuracy and generalization. This paper presents Geometric Mover's Light
(GMLight), a lighting estimation framework that employs a regression network
and a generative projector for effective illumination estimation. We
parameterize illumination scenes in terms of the geometric light distribution,
light …

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