no code implementations • ICCV 2017 • Andreas Schneider, Sandro Schonborn, Lavrenti Frobeen, Bernhard Egger, Thomas Vetter
Therefore, we propose to learn self-shadowing for Morphable Model parameters directly with a linear model.
no code implementations • 17 Jul 2019 • Bernhard Egger, Markus D. Schirmer, Florian Dubost, Marco J. Nardin, Natalia S. Rost, Polina Golland
We propose and demonstrate a joint model of anatomical shapes, image features and clinical indicators for statistical shape modeling and medical image analysis.
no code implementations • ICLR 2020 • Akash Srivastava, Yamini Bansal, Yukun Ding, Bernhard Egger, Prasanna Sattigeri, Josh Tenenbaum, David D. Cox, Dan Gutfreund
In this work, we tackle a slightly more intricate scenario where the observations are generated from a conditional distribution of some known control variate and some latent noise variate.
no code implementations • 25 Oct 2020 • Akash Srivastava, Yamini Bansal, Yukun Ding, Cole Lincoln Hurwitz, Kai Xu, Bernhard Egger, Prasanna Sattigeri, Joshua B. Tenenbaum, Phuong Le, Arun Prakash R, Nengfeng Zhou, Joel Vaughan, Yaquan Wang, Anwesha Bhattacharyya, Kristjan Greenewald, David D. Cox, Dan Gutfreund
Current autoencoder-based disentangled representation learning methods achieve disentanglement by penalizing the (aggregate) posterior to encourage statistical independence of the latent factors.
no code implementations • 4 Feb 2021 • Karthik Shetty, Annette Birkhold, Norbert Strobel, Bernhard Egger, Srikrishna Jaganathan, Markus Kowarschik, Andreas Maier
First, a statistical human shape model of the human anatomy and second, a differentiable X-ray renderer.
no code implementations • 28 Jul 2021 • Maximilian Weiherer, Andreas Eigenberger, Bernhard Egger, Vanessa Brébant, Lukas Prantl, Christoph Palm
We present the Regensburg Breast Shape Model (RBSM) -- a 3D statistical shape model of the female breast built from 110 breast scans acquired in a standing position, and the first publicly available.
no code implementations • 29 Sep 2021 • Bernhard Egger, Skylar Sutherland, Safa C. Medin, Joshua Tenenbaum
We demonstrate that non-orthogonality of the variation in identity and expression can cause identity-expression ambiguity in 3D Morphable Models, and that in practice expression and identity are far from orthogonal and can explain each other surprisingly well.
no code implementations • 1 Nov 2021 • Safa C. Medin, Bernhard Egger, Anoop Cherian, Ye Wang, Joshua B. Tenenbaum, Xiaoming Liu, Tim K. Marks
Recent advances in generative adversarial networks (GANs) have led to remarkable achievements in face image synthesis.
no code implementations • 30 Nov 2021 • Shubhaankar Gupta, Thomas P. O'Connell, Bernhard Egger
Pre-training on large-scale databases consisting of natural images and then fine-tuning them to fit the application at hand, or transfer-learning, is a popular strategy in computer vision.
no code implementations • 23 Jan 2022 • Moritz Drobnitzky, Jonas Friederich, Bernhard Egger, Patrick Zschech
Strong demand for autonomous vehicles and the wide availability of 3D sensors are continuously fueling the proposal of novel methods for 3D object detection.
no code implementations • 4 Mar 2022 • Skylar Sutherland, Bernhard Egger, Joshua Tenenbaum
We extend our model to a preliminary unsupervised learning framework that enables the learning of the distribution of 3D faces using one 3D template and a small number of 2D images.
no code implementations • 7 Jun 2022 • James A. D. Gardner, Bernhard Egger, William A. P. Smith
Training our model on a curated dataset of 1. 6K HDR environment maps of natural scenes, we compare it against traditional representations, demonstrate its applicability for an inverse rendering task and show environment map completion from partial observations.
no code implementations • 5 Aug 2022 • Richard Marcus, Niklas Knoop, Bernhard Egger, Marc Stamminger
Virtual testing is a crucial task to ensure safety in autonomous driving, and sensor simulation is an important task in this domain.
no code implementations • 27 Oct 2022 • Edith Tretschk, Navami Kairanda, Mallikarjun B R, Rishabh Dabral, Adam Kortylewski, Bernhard Egger, Marc Habermann, Pascal Fua, Christian Theobalt, Vladislav Golyanik
3D reconstruction of deformable (or non-rigid) scenes from a set of monocular 2D image observations is a long-standing and actively researched area of computer vision and graphics.
no code implementations • 29 Nov 2022 • Maximilian Weiherer, Finn Klein, Bernhard Egger
In this paper, we present a new method to qualitatively compare two linear SSMs in dense correspondence by computing approximate intersection spaces and set-theoretic differences between the (hyper-ellipsoidal) allowable shape domains spanned by the models.
no code implementations • 8 Mar 2023 • Karthik Shetty, Annette Birkhold, Srikrishna Jaganathan, Norbert Strobel, Bernhard Egger, Markus Kowarschik, Andreas Maier
Objective: A digital twin of a patient can be a valuable tool for enhancing clinical tasks such as workflow automation, patient-specific X-ray dose optimization, markerless tracking, positioning, and navigation assistance in image-guided interventions.
no code implementations • 17 Mar 2023 • Vanessa Wirth, Anna-Maria Liphardt, Birte Coppers, Johanna Bräunig, Simon Heinrich, Sigrid Leyendecker, Arnd Kleyer, Georg Schett, Martin Vossiek, Bernhard Egger, Marc Stamminger
Therefore, we propose ShaRPy, the first RGB-D Shape Reconstruction and hand Pose tracking system, which provides uncertainty estimates of the computed pose, e. g., when a finger is hidden or its estimate is inconsistent with the observations in the input, to guide clinical decision-making.
no code implementations • 15 Dec 2023 • Benno Buschmann, Andreea Dogaru, Elmar Eisemann, Michael Weinmann, Bernhard Egger
We demonstrate the compatibility and potential of our solution for both photo-realistic robust multi-view reconstruction from real-world images based on neural radiance fields and for single-shot reconstruction based on light-field networks.
no code implementations • 18 Mar 2024 • Mert Özer, Maximilian Weiherer, Martin Hundhausen, Bernhard Egger
Neural Radiance Fields (NeRFs) quickly evolved as the new de-facto standard for the task of novel view synthesis when trained on a set of RGB images.
no code implementations • 1 Apr 2024 • Maximilian Weiherer, Andreea Dogaru, Shreya Kapoor, Hannah Schieber, Bernhard Egger
What a wonderful ride it is!
no code implementations • 4 Apr 2024 • Andreea Dogaru, Mert Özer, Bernhard Egger
We therefore propose a hybrid method following a divide-and-conquer strategy.
1 code implementation • 20 Feb 2024 • Maximilian Hahn, Bernhard Egger
Statistical Shape Models of faces and various body parts are heavily used in medical image analysis, computer vision and visualization.
1 code implementation • 28 Nov 2023 • Benjamin Cappell, Andreas Stoll, Williams Chukwudi Umah, Bernhard Egger
In this work we aim at the very beginning of our visual experience - pre- and post-natal retinal waves which suggest to be a pre-training mechanism for the primate visual system at a very early stage of development.
1 code implementation • 12 Feb 2024 • Shiyu Li, Hannah Schieber, Niklas Corell, Bernhard Egger, Julian Kreimeier, Daniel Roth
Augmented reality assembly guidance requires 6D object poses of target objects in real time.
1 code implementation • 28 Nov 2023 • James A. D. Gardner, Evgenii Kashin, Bernhard Egger, William A. P. Smith
We also introduce a novel `outside-in' method for computing differentiable sky visibility based on a neural directional distance function.
1 code implementation • 15 Nov 2023 • James A. D. Gardner, Bernhard Egger, William A. P. Smith
Training our model on a curated dataset of 1. 6K HDR environment maps of natural scenes, we compare it against traditional representations, demonstrate its applicability for an inverse rendering task and show environment map completion from partial observations.
1 code implementation • 24 Nov 2020 • Skylar Sutherland, Bernhard Egger, Joshua Tenenbaum
We propose a method for constructing generative models of 3D objects from a single 3D mesh.
1 code implementation • 16 Mar 2023 • Hannah Schieber, Fabian Deuser, Bernhard Egger, Norbert Oswald, Daniel Roth
Current research on the joint optimization of camera parameters and NeRF focuses on refining noisy extrinsic camera parameters and often relies on the preprocessing of intrinsic camera parameters.
1 code implementation • CVPR 2023 • Karthik Shetty, Annette Birkhold, Srikrishna Jaganathan, Norbert Strobel, Markus Kowarschik, Andreas Maier, Bernhard Egger
Current techniques directly regress the shape, pose, and translation of a parametric model from an input image through a non-linear mapping with minimal flexibility to any external influences.
Ranked #2 on 3D Human Pose Estimation on 3DPW (using extra training data)
1 code implementation • 1 Apr 2023 • Maximilian Weiherer, Bernhard Egger
Finally, they end up as a researcher, writing boring, non-impressive papers all day long because they only rely on simple mathematics.
1 code implementation • CVPR 2023 • Chunlu Li, Andreas Morel-Forster, Thomas Vetter, Bernhard Egger, Adam Kortylewski
The main challenge is that the model fitting and the outlier segmentation are mutually dependent on each other, and need to be inferred jointly.
Ranked #4 on 3D Face Reconstruction on NoW Benchmark
2 code implementations • 5 Dec 2017 • Adam Kortylewski, Bernhard Egger, Andreas Schneider, Thomas Gerig, Andreas Morel-Forster, Thomas Vetter
4) We uncover a main limitation of current DCNN architectures, which is the difficulty to generalize when different identities to not share the same pose variation.
2 code implementations • 16 Feb 2018 • Adam Kortylewski, Andreas Schneider, Thomas Gerig, Bernhard Egger, Andreas Morel-Forster, Thomas Vetter
In our experiments with an off-the-shelf face recognition software we observe the following phenomena: 1) The amount of real training data needed to train competitive deep face recognition systems can be reduced significantly.
2 code implementations • 25 Sep 2017 • Thomas Gerig, Andreas Morel-Forster, Clemens Blumer, Bernhard Egger, Marcel Lüthi, Sandro Schönborn, Thomas Vetter
Non-rigid registration of faces is significant for many applications in computer vision, such as the construction of 3D Morphable face models (3DMMs).
1 code implementation • 19 Nov 2018 • Adam Kortylewski, Bernhard Egger, Andreas Morel-Forster, Andreas Schneider, Thomas Gerig, Clemens Blumer, Corius Reyneke, Thomas Vetter
We observe the following positive effects for face recognition and facial landmark detection tasks: 1) Priming with synthetic face images improves the performance consistently across all benchmarks because it reduces the negative effects of biases in the training data.
1 code implementation • CVPR 2020 • William A. P. Smith, Alassane Seck, Hannah Dee, Bernard Tiddeman, Joshua Tenenbaum, Bernhard Egger
In this paper, we bring together two divergent strands of research: photometric face capture and statistical 3D face appearance modelling.
1 code implementation • 25 Apr 2024 • Haomiao Ni, Bernhard Egger, Suhas Lohit, Anoop Cherian, Ye Wang, Toshiaki Koike-Akino, Sharon X. Huang, Tim K. Marks
To guide video generation with the additional image input, we propose a "repeat-and-slide" strategy that modulates the reverse denoising process, allowing the frozen diffusion model to synthesize a video frame-by-frame starting from the provided image.
1 code implementation • 3 Sep 2019 • Bernhard Egger, William A. P. Smith, Ayush Tewari, Stefanie Wuhrer, Michael Zollhoefer, Thabo Beeler, Florian Bernard, Timo Bolkart, Adam Kortylewski, Sami Romdhani, Christian Theobalt, Volker Blanz, Thomas Vetter
In this paper, we provide a detailed survey of 3D Morphable Face Models over the 20 years since they were first proposed.