English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

This paper solves the Sparse Photometric stereo through LightingInterpolation and Normal Estimation using a generative Network (SPLINE-Net).SPLINE-Net contains a lighting interpolation network to generate dense lightingobservations given a sparse set of lights as inputs followed by a normalestimation network to estimate surface normals. Both networks are jointlyconstrained by the proposed symmetric and asymmetric loss functions to enforceisotropic constrain and perform outlier rejection of global illuminationeffects. SPLINE-Net is verified to outperform existing methods for photometricstereo of general BRDFs by using only ten images of different lights instead ofusing nearly one hundred images.

SPLINE-Net: Sparse Photometric Stereo through Lighting Interpolation and Normal Estimation Networks