2 citations · 4 across the 3 of their papers we have counts for
4 papers · 1 filter
Towards Fast and Scalable Normal Integration using Continuous Components
Francesco Milano, Jen Jen Chung, Lionel Ott +1
Surface normal integration is a fundamental problem in computer vision, dealing with the objective of reconstructing a surface from its corresponding normal map. Existing approache…
Discontinuity-aware Normal Integration for Generic Central Camera Models
Francesco Milano, Manuel López-Antequera, Naina Dhingra +2
Recovering a 3D surface from its surface normal map, a problem known as normal integration, is a key component for photometric shape reconstruction techniques such as shape-from-sh…
NeuSurfEmb: A Complete Pipeline for Dense Correspondence-based 6D Object Pose Estimation without CAD Models
Francesco Milano, Jen Jen Chung, Hermann Blum +2
State-of-the-art approaches for 6D object pose estimation assume the availability of CAD models and require the user to manually set up physically-based rendering (PBR) pipelines f…
Zero123-6D: Zero-shot Novel View Synthesis for RGB Category-level 6D Pose Estimation
Francesco Di Felice, Alberto Remus, Stefano Gasperini +5
Estimating the pose of objects through vision is essential to make robotic platforms interact with the environment. Yet, it presents many challenges, often related to the lack of f…