SOURCE-LINKED INTELLIGENCE

EliGSiR: Continual RGB-D Mapping with Gaussian Splatting under Bounded Compute

arXiv · AI, language, vision and robotics · article · Sep 17, 2026 · UTC

Conventional 3D Gaussian Splatting assumes a closed set of observations and long optimization schedules. Continual RGB-D mapping in contrast poses the problem that new observations arrive online, while previously reconstructed regions must be preserved. We present EliGSiR (Evidence-guided Load-adaptive Incremental Gaussian Splatting with Image Replay), a continual Gaussian mapper that controls how the available optimization budget is used as the reconstruction evolves. Map-Guided View Scheduling filters redundant incoming views and reconsiders retained views according to the current state of t

Read original source ↗ Open in workspace

recordType

paper

region

Global