1 code implementation • 5 Sep 2024 • Shashank Tripathi, Omid Taheri, Christoph Lassner, Michael J. Black, Daniel Holden, Carsten Stoll
Generating realistic human motion is essential for many computer vision and graphics applications.
no code implementations • 28 Jun 2024 • Nicola Garau, Giulia Martinelli, Niccolò Bisagno, Denis Tomè, Carsten Stoll
These inputs are obtained from RegNet, which starts from a single image and provides estimates for the 2D pose and camera parameters.
no code implementations • 15 Jun 2024 • Yi Hua, Christoph Lassner, Carsten Stoll, Iain Matthews
In recent years, the development of Neural Radiance Fields has enabled a previously unseen level of photo-realistic 3D reconstruction of scenes and objects from multi-view camera data.
no code implementations • 18 Mar 2024 • Tom Wehrbein, Bodo Rosenhahn, Iain Matthews, Carsten Stoll
To address this issue, we propose to construct dense correspondences between initial human model estimates and the corresponding images that can be used to refine the initial predictions.
no code implementations • CVPR 2022 • Salvador Medina, Denis Tome, Carsten Stoll, Mark Tiede, Kevin Munhall, Alexander G. Hauptmann, Iain Matthews
In this work, we introduce a large-scale speech and mocap dataset that focuses on capturing tongue, jaw, and lip motion.
no code implementations • CVPR 2021 • Amit Raj, Julian Tanke, James Hays, Minh Vo, Carsten Stoll, Christoph Lassner
The combination of traditional rendering with neural networks in Deferred Neural Rendering (DNR) provides a compelling balance between computational complexity and realism of the resulting images.
no code implementations • ECCV 2020 • Edgar Tretschk, Ayush Tewari, Vladislav Golyanik, Michael Zollhöfer, Carsten Stoll, Christian Theobalt
At the level of patches, objects across different categories share similarities, which leads to more generalizable models.
no code implementations • ECCV 2020 • Tiancheng Zhi, Christoph Lassner, Tony Tung, Carsten Stoll, Srinivasa G. Narasimhan, Minh Vo
We present TexMesh, a novel approach to reconstruct detailed human meshes with high-resolution full-body texture from RGB-D video.