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

While numerous 3D reconstruction and novel-view synthesis methods allow forphotorealistic rendering of a scene from multi-view images easily captured withconsumer cameras, they bake illumination in their representations and fallshort of supporting advanced applications like material editing, relighting,and virtual object insertion. The reconstruction of physically based materialproperties and lighting via inverse rendering promises to enable suchapplications.  However, most inverse rendering techniques require high dynamic range (HDR)images as input, a setting that is inaccessible to most users. We present amethod that recovers the physically based material properties andspatially-varying HDR lighting of a scene from multi-view, low-dynamic-range(LDR) images. We model the LDR image formation process in our inverse renderingpipeline and propose a novel optimization strategy for material, lighting, anda camera response model. We evaluate our approach with synthetic and realscenes compared to the state-of-the-art inverse rendering methods that takeeither LDR or HDR input. Our method outperforms existing methods taking LDRimages as input, and allows for highly realistic relighting and objectinsertion.

IRIS: Inverse Rendering of Indoor Scenes from Low Dynamic Range Images