12 citations · 22 across the 18 of their papers we have counts for
4 papers · 1 filter
GRMM: Real-Time High-Fidelity Gaussian Morphable Head Model with Learned Residuals
Mohit Mendiratta, Mayur Deshmukh, Kartik Teotia +3
3D Morphable Models (3DMMs) enable controllable facial geometry and expression editing for reconstruction, animation, and AR/VR, but traditional PCA-based mesh models are limited i…
CNS-Bench: Benchmarking Image Classifier Robustness Under Continuous Nuisance Shifts
Olaf Dünkel, Artur Jesslen, Jiahao Xie +3
An important challenge when using computer vision models in the real world is to evaluate their performance in potential out-of-distribution (OOD) scenarios. While simple synthetic…
Do It Yourself: Learning Semantic Correspondence from Pseudo-Labels
Olaf Dünkel, Thomas Wimmer, Christian Theobalt +2
Finding correspondences between semantically similar points across images and object instances is one of the everlasting challenges in computer vision. While large pre-trained visi…
Common3D: Self-Supervised Learning of 3D Morphable Models for Common Objects in Neural Feature Space
Leonhard Sommer, Olaf Dünkel, Christian Theobalt +1
3D morphable models (3DMMs) are a powerful tool to represent the possible shapes and appearances of an object category. Given a single test image, 3DMMs can be used to solve variou…