337 citations · 1.3k across the 62 of their papers we have counts for
22 papers · 1 filter
Panoptic Lifting for 3D Scene Understanding with Neural Fields
Yawar Siddiqui, Lorenzo Porzi, Samuel Rota Buló +4
We propose Panoptic Lifting, a novel approach for learning panoptic 3D volumetric representations from images of in-the-wild scenes. Once trained, our model can render color images…
SPARF: Large-Scale Learning of 3D Sparse Radiance Fields from Few Input Images
Abdullah Hamdi, Bernard Ghanem, Matthias Nießner
Recent advances in Neural Radiance Fields (NeRFs) treat the problem of novel view synthesis as Sparse Radiance Field (SRF) optimization using sparse voxels for efficient and fast r…
Learning Neural Parametric Head Models
Simon Giebenhain, Tobias Kirschstein, Markos Georgopoulos +3
We propose a novel 3D morphable model for complete human heads based on hybrid neural fields. At the core of our model lies a neural parametric representation that disentangles ide…
ObjectMatch: Robust Registration using Canonical Object Correspondences
Can Gümeli, Angela Dai, Matthias Nießner
We present ObjectMatch, a semantic and object-centric camera pose estimator for RGB-D SLAM pipelines. Modern camera pose estimators rely on direct correspondences of overlapping re…
ClipFace: Text-guided Editing of Textured 3D Morphable Models
Shivangi Aneja, Justus Thies, Angela Dai +1
We propose ClipFace, a novel self-supervised approach for text-guided editing of textured 3D morphable model of faces. Specifically, we employ user-friendly language prompts to ena…
DiffRF: Rendering-Guided 3D Radiance Field Diffusion
Norman Müller, Yawar Siddiqui, Lorenzo Porzi +3
We introduce DiffRF, a novel approach for 3D radiance field synthesis based on denoising diffusion probabilistic models. While existing diffusion-based methods operate on images, l…