Orazio Gallo

Papers

Total Citations

157

H-Index

About

Orazio Gallo is a leading researcher in computer vision and computational photography, whose work bridges geometric understanding and 3D scene reconstruction. His most influential contribution, the CC-RANSAC algorithm (2010, 121 citations), revolutionized plane fitting in range data by robustly handling multiple surfaces—a foundational tool for 3D mapping and robotics. Gallo’s recent work pushes boundaries in articulated object manipulation: his 2022 paper “Watch It Move” (32 citations) introduced an unsupervised method to discover 3D joints from video, enabling re-posing of objects for virtual reality and animation without manual annotation. He also tackles practical challenges in depth estimation with FoVA-Depth (2024, 4 citations), which achieves field-of-view-agnostic depth prediction across diverse camera setups—critical for automotive and robotics applications where wide-angle cameras are standard. Gallo’s research consistently addresses real-world constraints, from noisy sensor data to varying camera geometries, making his work highly cited and applied. His ability to combine theoretical rigor with deployable solutions has established him as a key figure in 3D vision, with ongoing impact on autonomous systems and interactive graphics.