20 citations · 47 across the 6 of their papers we have counts for
6 papers
L3DG: Latent 3D Gaussian Diffusion
Barbara Roessle, Norman Müller, Lorenzo Porzi +4
We propose L3DG, the first approach for generative 3D modeling of 3D Gaussians through a latent 3D Gaussian diffusion formulation. This enables effective generative 3D modeling, sc…
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…
GANeRF: Leveraging Discriminators to Optimize Neural Radiance Fields
Barbara Roessle, Norman Müller, Lorenzo Porzi +3
Neural Radiance Fields (NeRF) have shown impressive novel view synthesis results; nonetheless, even thorough recordings yield imperfections in reconstructions, for instance due to…
End2End Multi-View Feature Matching with Differentiable Pose Optimization
Barbara Roessle, Matthias Nießner
Erroneous feature matches have severe impact on subsequent camera pose estimation and often require additional, time-costly measures, like RANSAC, for outlier rejection. Our method…
Dense Depth Priors for Neural Radiance Fields from Sparse Input Views
Barbara Roessle, Jonathan T. Barron, Ben Mildenhall +2
Neural radiance fields (NeRF) encode a scene into a neural representation that enables photo-realistic rendering of novel views. However, a successful reconstruction from RGB image…