Reconstruct Scene (Pi3)

How it fits

Typical backends

Caveats

• Hard constraintAt least two overlapping views of the same scene are needed per tick; the model has no privileged reference view, but a single view gives a degenerate pose and non-overlapping views reconstruct poorly.
• AccuracyGeometry is scale-invariant rather than metric, and no camera intrinsics are regressed — only poses, world point maps, and the fused cloud — so calibrate against a known distance when absolute scale matters.
• I/O contractPer-view outputs are produced at a shared downscaled grid bounded by a per-view pixel budget, not the source resolution; the confidence floor (a 0-to-1 probability) and the point cap apply only to the fused PointCloud arm.
• CostReconstruction is GPU-heavy and memory scales with the view count and the per-view pixel budget, which is the main lever for large images; the per-tick view count is capped to bound peak memory.
• State lifetimeThe model and weights are loaded once at startup, downloading from the model hub on a cold container, so the first batch needs outbound network.