EliGSiR: Continual RGB-D Mapping with Gaussian Splatting under Bounded Compute
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 the map. Load-Adaptive Fidelity adjusts supervision resolution to the current mapping load instead...
| Authors | Björn Ellensohn, Elmar Rueckert, Christian Rauch |
|---|---|
| Primary category | cs.CV |
| Published | 17 September 2026 |
| Last updated at source | 17 September 2026 |
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