We propose scene-adaptive strategies to efficiently allocate representation capacity for generating immersive experiences of indoor environments from incomplete observations. Indoor scenes with multiple rooms often exhibit irregular layouts with varying complexity, containing clutter, occlusion, and flat walls. We maximize the utilization of limited resources with guidance from geometric priors, which are often readily available after pre-processing stages. We record observation statistics on the estimated geometric scaffold and guide the optimal placement of bases, which greatly improves upon the uniform basis arrangements adopted by previous scalable scene representations. We also suggest scene-adaptive virtual viewpoints to compensate for geometric deficiencies inherent in view configurations in the input trajectory and impose the necessary regularization. We present a comprehensive analysis and discussion regarding rendering quality and memory requirements in several large-scale indoor scenes, demonstrating significant enhancements compared to baselines that employ regular placements.
Building similarity graph...
Analyzing shared references across papers
Loading...
Minkwan Kim
Changwoon Choi
Young Min Kim
IEEE Transactions on Visualization and Computer Graphics
Seoul National University
Building similarity graph...
Analyzing shared references across papers
Loading...
Kim et al. (Thu,) studied this question.
www.synapsesocial.com/papers/69fd7ddcbfa21ec5bbf0620b — DOI: https://doi.org/10.1109/tvcg.2026.3690462