3 citations · 4 across the 7 of their papers we have counts for
11 papers
Diff3R: Feed-forward 3D Gaussian Splatting with Uncertainty-aware Differentiable Optimization
Yueh-Cheng Liu, Jozef Hladký, Matthias Nießner +1
Recent advances in 3D Gaussian Splatting (3DGS) present two main directions: feed-forward models offer fast inference in sparse-view settings, while per-scene optimization yields h…
Seen2Scene: Completing Realistic 3D Scenes with Visibility-Guided Flow
Quan Meng, Yujin Chen, Lei Li +2
We present Seen2Scene, the first flow matching-based approach that trains directly on incomplete, real-world 3D scans for scene completion and generation. Unlike prior methods that…
Intrinsic Image Fusion for Multi-View 3D Material Reconstruction
Peter Kocsis, Lukas Höllein, Matthias Nießner
We introduce Intrinsic Image Fusion, a method that reconstructs high-quality physically based materials from multi-view images. Material reconstruction is highly underconstrained a…
WorldExplorer: Towards Generating Fully Navigable 3D Scenes
Manuel-Andreas Schneider, Lukas Höllein, Matthias Nießner
Generating 3D worlds from text is a highly anticipated goal in computer vision. Existing works are limited by the degree of exploration they allow inside of a scene, i.e., produce…
TUM2TWIN: Introducing the Large-Scale Multimodal Urban Digital Twin Benchmark Dataset
Olaf Wysocki, Benedikt Schwab, Manoj Kumar Biswanath +31
Urban Digital Twins (UDTs) have become essential for managing cities and integrating complex, heterogeneous data from diverse sources. Creating UDTs involves challenges at multiple…
QuickSplat: Fast 3D Surface Reconstruction via Learned Gaussian Initialization
Yueh-Cheng Liu, Lukas Höllein, Matthias Nießner +1
Surface reconstruction is fundamental to computer vision and graphics, enabling applications in 3D modeling, mixed reality, robotics, and more. Existing approaches based on volumet…
IntrinsiX: High-Quality PBR Generation using Image Priors
Peter Kocsis, Lukas Höllein, Matthias Nießner
We introduce IntrinsiX, a novel method that generates high-quality intrinsic images from text description. In contrast to existing text-to-image models whose outputs contain baked-…
Animating the Uncaptured: Humanoid Mesh Animation with Video Diffusion Models
Marc Benedí San Millán, Angela Dai, Matthias Nießner
Animation of humanoid characters is essential in various graphics applications, but requires significant time and cost to create realistic animations. We propose an approach to syn…
MeshPad: Interactive Sketch-Conditioned Artist-Reminiscent Mesh Generation and Editing
Haoxuan Li, Ziya Erkoc, Lei Li +4
We introduce MeshPad, a generative approach that creates 3D meshes from sketch inputs. Building on recent advances in artist-reminiscent triangle mesh generation, our approach addr…
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…
Intrinsic Image Diffusion for Indoor Single-view Material Estimation
Peter Kocsis, Vincent Sitzmann, Matthias Nießner
We present Intrinsic Image Diffusion, a generative model for appearance decomposition of indoor scenes. Given a single input view, we sample multiple possible material explanations…