Prof. Dr. Bernhard Egger

Juniorprofessur für Cognitive Computer Vision (Stiftungsprofessur)

Deep Learning Compatible Differentiable X-ray Projections for Inverse Rendering (2021) Shetty K, Birkhold A, Strobel N, Egger B, Jaganathan S, Kowarschik M, Maier A Conference contribution 3D Morphable Face Modelsa-Past, Present, and Future (2020) Egger B, Smith WAP, Tewari A, Wuhrer S, Zollhoefer M, Beeler T, Bernard F, et al. Journal article A morphable face Albedo model (2020) Smith WAP, Seck A, Dee H, Tiddeman B, Tenenbaum JB, Egger B Conference contribution Analyzing and reducing the damage of dataset bias to face recognition with synthetic data (2019) Kortylewski A, Egger B, Schneider A, Gerig T, Morel-Forster A, Vetter T Conference contribution Patient-specific conditional joint models of shape, image features and clinical indicators (2019) Egger B, Schirmer MD, Dubost F, Nardin MJ, Rost NS, Golland P Conference contribution Empirically analyzing the effect of dataset biases on deep face recognition systems (2018) Kortylewski A, Egger B, Schneider A, Gerig T, Morel-Forster A, Vetter T Conference contribution Occlusion-Aware 3D Morphable Models and an Illumination Prior for Face Image Analysis (2018) Egger B, Schonborn S, Schneider A, Kortylewski A, Morel-Forster A, Blumer C, Vetter T Journal article Morphable face models - An open framework (2018) Gerig T, Morel-Forster A, Blumer C, Egger B, Luthi M, Schonborn S, Vetter T Conference contribution, Conference Contribution A parametric freckle model for faces (2018) Schneider A, Egger B, Vetter T Conference contribution Efficient Global Illumination for Morphable Models (2017) Schneider A, Schonborn S, Egger B, Frobeen L, Vetter T Conference contribution