CLoSeR: Closing the Loop for Long-Context Streaming Reconstruction
This preprint presents CLoSeR, a loop-closure system built on the streaming feedforward reconstructor LoGeR for long monocular videos. It detects revisits with global image descriptors, re-runs the backbone on loop-conditioned windows, and optimizes all poses on SE(3), cutting average trajectory error substantially on kilometer-scale benchmarks (e.g., 11.15 m vs 36.16 m for LoGeR on VBR). Because the backbone already has consistent global scale, this avoids the fragile point-cloud alignment and higher-dimensional pose graph optimization used by earlier submap methods.