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

The reconstruction of object surfaces from multi-view images or monocularvideo is a fundamental issue in computer vision. However, much of the recentresearch concentrates on reconstructing geometry through implicit or explicitmethods. In this paper, we shift our focus towards reconstructing mesh inconjunction with color. We remove the view-dependent color from neural volumerendering while retaining volume rendering performance through a relightingnetwork. Mesh is extracted from the signed distance function (SDF) network forthe surface, and color for each surface vertex is drawn from the global colornetwork. To evaluate our approach, we conceived a in hand object scanning taskfeaturing numerous occlusions and dramatic shifts in lighting conditions. We'vegathered several videos for this task, and the results surpass those of anyexisting methods capable of reconstructing mesh alongside color. Additionally,our method's performance was assessed using public datasets, including DTU,BlendedMVS, and OmniObject3D. The results indicated that our method performswell across all these datasets. Project page:https://colmar-zlicheng.github.io/color_neus.

Color-NeuS: Reconstructing Neural Implicit Surfaces with Color