C3DPO: Canonical 3D pose networks for non-rigid structure from motion
We propose C3DPO, a method for extracting 3D models of deformable objects from 2D keypoint annotations in unconstrained images. We do so by learning a deep network that reconstructs a 3D object from a single view at a time, accounting for partial occlusions, and explicitly factoring the effects of v...
| Main Authors: | , , , , |
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| Format: | Conference item |
| Published: |
2020
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