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/

Zendy Plus

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

Zendy Tools

Zendy Open

Designing a 3D game scene is a tedious task that often requires a substantialamount of work. Typically, this task involves synthesis, coloring, andplacement of 3D models within the game scene. To lessen this workload, we canapply machine learning to automate some aspects of the game scene development.Earlier research has already tackled automated generation of the game scenebackground with machine learning. However, model auto-coloring remains anunderexplored problem. The automatic coloring of a 3D model is a challengingtask, especially when dealing with the digital representation of a colorful,multipart object. In such a case, we have to ``understand'' the object'scomposition and coloring scheme of each part. Existing single-stage methodshave their own caveats such as the need for segmentation of the object orgenerating individual parts that have to be assembled together to yield thefinal model. We address these limitations by proposing a two-stage trainingapproach to synthesize auto-colored 3D models. In the first stage, we obtain a3D point cloud representing a 3D object, whilst in the second stage, we assigncolors to points within such cloud. Next, by leveraging the so-calledtriangulation trick, we generate a 3D mesh in which the surfaces are coloredbased on interpolation of colored points representing vertices of a given meshtriangle. This approach allows us to generate a smooth coloring scheme.Experimental evaluation shows that our two-stage approach gives better resultsin terms of shape reconstruction and coloring when compared to traditionalsingle-stage techniques.

HyperColor: A HyperNetwork Approach for Synthesizing Auto-colored 3D Models for Game Scenes Population