3D Reconstruction Completion Using Per-Object Priors
Lead Research Organisation:
Imperial College London
Department Name: Computing
Abstract
Knowledge of 3D scene geometry, including the structure of unobserved regions, is critically important to robotics, with applications in manipulator grasp planning and free space mapping. This thesis proposes novel approaches on using learning-based priors for per-object reconstructions, allowing for scalable multi-view reconstructions of entire scenes.
computer vision
computer vision
Organisations
People |
ORCID iD |
| Andrea Nicastro (Student) |
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| EP/N509206/1 | 30/09/2015 | 29/09/2021 | |||
| 2637948 | Studentship | EP/N509206/1 | 30/09/2015 | 29/09/2019 | Andrea Nicastro |