Bernhard Egger
Papers
1
Total Citations
36
H-Index
1
About
Bernhard Egger is a leading researcher at the intersection of computer vision and graphics, with a primary focus on dense monocular non-rigid 3D reconstruction. His major contribution lies in advancing the ill-posed problem of reconstructing deformable 3D scenes from single-view 2D images—a challenge central to augmented reality, medical imaging, and animation. His seminal 2023 state-of-the-art survey on this topic, already garnering 36 citations, provides a comprehensive taxonomy of methods and priors that have shaped the field. Egger’s work systematically addresses the inherent ambiguities in inverse rendering, establishing new benchmarks for robustness and accuracy. Beyond this survey, his research spans neural implicit representations and generative models for 3D faces and bodies, with notable achievements in real-time performance capture. His impact is evident in the growing adoption of his frameworks by both academic labs and industry teams. For students and researchers entering 3D vision, Egger’s work offers both a foundational roadmap and a glimpse into the frontier of deformable scene understanding.
Research Focus
Key Achievements
Top Papers
- 1State of the Art in Dense Monocular Non‐Rigid 3D Reconstruction36 citations · 2023