no code implementations • 24 May 2024 • Jorge Condor, Sebastien Speierer, Lukas Bode, Aljaz Bozic, Simon Green, Piotr Didyk, Adrian Jarabo
Inspired by recent methods for scene reconstruction that leverage mixtures of 3D Gaussians to model radiance fields, we formalize and generalize the modeling of scattering and emissive media using mixtures of simple kernel-based volumetric primitives.
no code implementations • 13 Feb 2024 • Michael Fischer, Zhengqin Li, Thu Nguyen-Phuoc, Aljaz Bozic, Zhao Dong, Carl Marshall, Tobias Ritschel
A Neural Radiance Field (NeRF) encodes the specific relation of 3D geometry and appearance of a scene.
no code implementations • 14 Dec 2023 • Ziyan Wang, Giljoo Nam, Aljaz Bozic, Chen Cao, Jason Saragih, Michael Zollhoefer, Jessica Hodgins
In this paper, we present a novel method for creating high-fidelity avatars with diverse hairstyles.
no code implementations • 16 Aug 2023 • Edith Tretschk, Vladislav Golyanik, Michael Zollhoefer, Aljaz Bozic, Christoph Lassner, Christian Theobalt
We propose SceNeRFlow to reconstruct a general, non-rigid scene in a time-consistent manner.
no code implementations • 15 Jun 2023 • Shizhan Zhu, Shunsuke Saito, Aljaz Bozic, Carlos Aliaga, Trevor Darrell, Christop Lassner
Reconstructing and relighting objects and scenes under varying lighting conditions is challenging: existing neural rendering methods often cannot handle the complex interactions between materials and light.
1 code implementation • CVPR 2020 • Aljaz Bozic, Michael Zollhofer, Christian Theobalt, Matthias Niessner
Applying data-driven approaches to non-rigid 3D reconstruction has been difficult, which we believe can be attributed to the lack of a large-scale training corpus.