1.2k citations · 4.7k across the 165 of their papers we have counts for
16 papers · 1 filter
Learning a Disentangled Embedding for Monocular 3D Shape Retrieval and Pose Estimation
Kyaw Zaw Lin, Weipeng Xu, Qianru Sun +2
We propose a novel approach to jointly perform 3D shape retrieval and pose estimation from monocular images.In order to make the method robust to real-world image variations, e.g.…
FML: Face Model Learning from Videos
Ayush Tewari, Florian Bernard, Pablo Garrido +6
Monocular image-based 3D reconstruction of faces is a long-standing problem in computer vision. Since image data is a 2D projection of a 3D face, the resulting depth ambiguity make…
On Implicit Filter Level Sparsity in Convolutional Neural Networks
Dushyant Mehta, Kwang In Kim, Christian Theobalt
We investigate filter level sparsity that emerges in convolutional neural networks (CNNs) which employ Batch Normalization and ReLU activation, and are trained with adaptive gradie…
IGNOR: Image-guided Neural Object Rendering
Justus Thies, Michael Zollhöfer, Christian Theobalt +2
We propose a learned image-guided rendering technique that combines the benefits of image-based rendering and GAN-based image synthesis. The goal of our method is to generate photo…
Higher-order Projected Power Iterations for Scalable Multi-Matching
Florian Bernard, Johan Thunberg, Paul Swoboda +1
The matching of multiple objects (e.g. shapes or images) is a fundamental problem in vision and graphics. In order to robustly handle ambiguities, noise and repetitive patterns in…
LiveCap: Real-time Human Performance Capture from Monocular Video
Marc Habermann, Weipeng Xu, Michael Zollhoefer +2
We present the first real-time human performance capture approach that reconstructs dense, space-time coherent deforming geometry of entire humans in general everyday clothing from…