BUILD-A-VOLCAP: AUTOMATED SYNTHETIC VALIDATION OF REAL-WORLD VOLUMETRIC CAPTURE QUALITY

Volumetric capture techniques have significantly advanced in recent years, enabling detailed 3D reconstructions of dynamic real-world scenes. However, predicting their performance prior to real-world deployment remains challenging, often leading to costly experimental setups and uncertain outcomes. In this paper, we present Build-A-Volcap, an automated synthetic validation environment designed to predict the quality of real-world volumetric capture systems. Our solution constructs comprehensive synthetic datasets and environments that faithfully simulate practical capture conditions. This enables rigorous testing and benchmarking of volumetric methods such as photogrammetry, NeRF, Gaussian Splatting and Radiant Foam without the need for physical setups. Through extensive experiments, we demonstrate how Build-A-Volcap effectively identifies methodological strengths and limitations, significantly reducing the synthetic-to-real gap. Our pipeline enables researchers and companies to optimize and validate their volumetric capture setups virtually, ensuring robust performance upon real-world deployment. More information and code release on our project page: https://mmlab-cv.github.io/Build-A-Volcap/.