activity
20202026
most citedAutoRF: Learning 3D Object Radiance Fields from Single View Observations

2 citations · 2 across the 3 of their papers we have counts for

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8 papers · 1 filter

cs.CV2026

LuxRemix: Lighting Decomposition and Remixing for Indoor Scenes

Ruofan Liang, Norman Müller, Ethan Weber +4

We present a novel approach for interactive light editing in indoor scenes from a single multi-view scene capture. Our method leverages a generative image-based light decomposition…

cs.CV2025

Easy3D: A Simple Yet Effective Method for 3D Interactive Segmentation

Andrea Simonelli, Norman Müller, Peter Kontschieder

The increasing availability of digital 3D environments, whether through image-based 3D reconstruction, generation, or scans obtained by robots, is driving innovation across various…

cs.CV2025

Generative Gaussian Splatting: Generating 3D Scenes with Video Diffusion Priors

Katja Schwarz, Norman Mueller, Peter Kontschieder

Synthesizing consistent and photorealistic 3D scenes is an open problem in computer vision. Video diffusion models generate impressive videos but cannot directly synthesize 3D repr…

cs.CV2024

Coherent 3D Scene Diffusion From a Single RGB Image

Manuel Dahnert, Angela Dai, Norman Müller +1

We present a novel diffusion-based approach for coherent 3D scene reconstruction from a single RGB image. Our method utilizes an image-conditioned 3D scene diffusion model to simul…

cs.CV2024

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…

cs.CV2023

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…