16 citations · 23 across the 5 of their papers we have counts for
14 papers
G3DST: Generalizing 3D Style Transfer with Neural Radiance Fields across Scenes and Styles
Adil Meric, Umut Kocasari, Matthias Nießner +1
Neural Radiance Fields (NeRF) have emerged as a powerful tool for creating highly detailed and photorealistic scenes. Existing methods for NeRF-based 3D style transfer need extensi…
Robust 3D Gaussian Splatting for Novel View Synthesis in Presence of Distractors
Paul Ungermann, Armin Ettenhofer, Matthias Nießner +1
3D Gaussian Splatting has shown impressive novel view synthesis results; nonetheless, it is vulnerable to dynamic objects polluting the input data of an otherwise static scene, so…
MultiDiff: Consistent Novel View Synthesis from a Single Image
Norman Müller, Katja Schwarz, Barbara Roessle +4
We introduce MultiDiff, a novel approach for consistent novel view synthesis of scenes from a single RGB image. The task of synthesizing novel views from a single reference image i…
LightIt: Illumination Modeling and Control for Diffusion Models
Peter Kocsis, Julien Philip, Kalyan Sunkavalli +2
We introduce LightIt, a method for explicit illumination control for image generation. Recent generative methods lack lighting control, which is crucial to numerous artistic aspect…
Motion2VecSets: 4D Latent Vector Set Diffusion for Non-rigid Shape Reconstruction and Tracking
Wei Cao, Chang Luo, Biao Zhang +2
We introduce Motion2VecSets, a 4D diffusion model for dynamic surface reconstruction from point cloud sequences. While existing state-of-the-art methods have demonstrated success i…
Generating Context-Aware Natural Answers for Questions in 3D Scenes
Mohammed Munzer Dwedari, Matthias Niessner, Dave Zhenyu Chen
3D question answering is a young field in 3D vision-language that is yet to be explored. Previous methods are limited to a pre-defined answer space and cannot generate answers natu…