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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…