AI RESEARCH
LoGeR: Long-Context Geometric Reconstruction with Hybrid Memory
arXiv CS.LG
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ArXi:2603.03269v2 Announce Type: replace-cross Feedforward geometric foundation models achieve strong short-window reconstruction, yet scaling them to minutes-long videos is bottlenecked by quadratic attention complexity or limited effective memory in recurrent designs. We present LoGeR (Long-context Geometric Reconstruction), a novel architecture that scales dense 3D reconstruction to extremely long sequences without post-optimization. LoGeR processes video streams in chunks, leveraging strong bidirectional priors for high-fidelity intra-chunk reasoning.