Repairing Shape-Prior Shortcuts in Long-Range Single-Shot Fringe Projection Profilometry
Single-shot fringe projection profilometry (FPP) networks that regress depth directly can exploit a shape-prior shortcut, recovering depth from object boundaries rather than from fringe phase. On a photorealistic synthetic benchmark (15,600 fringe images, 50 objects at 1.5-2.1 m standoff), the best such UNet baseline plateaus at 14.54 mm object mean absolute error (MAE), and neither more data nor more capacity removes the shortcut, because neither changes the hypothesis space the optimizer searches. We introduce PhiCalNet, which outputs a wrapped-phase representation $(\sinφ, \cosφ)$ and maps it to depth through a fixed differentiable calibration layer, removing the shape-prior solution a...
| Authors | Adam Haroon, Cody Fleming, Beiwen Li |
|---|---|
| Primary category | cs.LG |
| Published | 10 July 2026 |
| Last updated at source | 10 July 2026 |
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