Data fidelity
Capture quality you can see
Reconstruction quality is decided at capture time. Move slowly around an object with plenty of overlap and you get dense, complete geometry. A quick casual pass leaves gaps: sparse points, noise, whole regions never seen. Here is the same ceramic mug captured both ways, in true colour. Drag to orbit; turn the casual capture to find the side it never saw.
Illustrative demoBoth clouds are the same scanned object in real per-point colour. The casual capture is a simulated degradation (subsampled, noised, and clipped on one side) to show a coverage gap, not two separate field captures.
- points
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- coverage
- partial · one side missing
- points
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- coverage
- complete · all sides
- Low view overlap
- Surfaces seen in too few frames stay sparse and noisy.
- Unvisited angles
- A side you never walk around never gets reconstructed.
- Fast, shaky motion
- Motion blur and weak parallax thin out the cloud.
Deliberate, multi-view capture returns dense, complete geometry you can train on. A casual pass returns sparse, holey clouds: the gaps a policy can't learn from, and the regions a refinement pass has to re-observe before data ships.
Demo object: “Cole Hardware Mug Classic Blue,” Google Scanned Objects, © Google LLC, CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/).