47 citations · 131 across the 26 of their papers we have counts for
38 papers
Map-Det3D: Metric Feed-Forward 3D Reconstruction Prior for Multi-view 3D Object Detection from Streaming Inputs
Yung-Hsu Yang, Luigi Piccinelli, Samuel Rota Bulò +7
Metric 3D object detection is a core capability for embodied agents, yet most reliable systems lean on depth sensors, trading away cost, power, and integration simplicity. This mot…
Learn2Splat: Extending the Horizon of Learned 3DGS Optimization
Naama Pearl, Stefano Esposito, Haofei Xu +6
3D Gaussian Splatting (3DGS) optimization is most commonly performed using general-purpose first-order optimizers such as Adam or SGD. Although robust across scenes, they update ea…
DRoPS: Dynamic 3D Reconstruction of Pre-Scanned Objects
Narek Tumanyan, Samuel Rota Bulò, Denis Rozumny +5
Dynamic scene reconstruction from casual videos has seen recent remarkable progress. Numerous approaches have attempted to overcome the ill-posedness of the task by distilling prio…
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…
MapAnything: Universal Feed-Forward Metric 3D Reconstruction
Nikhil Keetha, Norman Müller, Johannes Schönberger +14
We introduce MapAnything, a unified transformer-based feed-forward model that ingests one or more images along with optional geometric inputs such as camera intrinsics, poses, dept…
BulletGen: Improving 4D Reconstruction with Bullet-Time Generation
Denis Rozumny, Jonathon Luiten, Numair Khan +2
Transforming casually captured, monocular videos into fully immersive dynamic experiences is a highly ill-posed task, and comes with significant challenges, e.g., reconstructing un…
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…
FlowR: Flowing from Sparse to Dense 3D Reconstructions
Tobias Fischer, Samuel Rota Bulò, Yung-Hsu Yang +7
3D Gaussian splatting enables high-quality novel view synthesis (NVS) at real-time frame rates. However, its quality drops sharply as we depart from the training views. Thus, dense…
A Recipe for Generating 3D Worlds From a Single Image
Katja Schwarz, Denys Rozumnyi, Samuel Rota Bulò +2
We introduce a recipe for generating immersive 3D worlds from a single image by framing the task as an in-context learning problem for 2D inpainting models. This approach requires…
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…
Hardware-Rasterized Ray-Based Gaussian Splatting
Samuel Rota Bulò, Nemanja Bartolovic, Lorenzo Porzi +1
We present a novel, hardware rasterized rendering approach for ray-based 3D Gaussian Splatting (RayGS), obtaining both fast and high-quality results for novel view synthesis. Our w…
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…
Volumetric Surfaces: Representing Fuzzy Geometries with Layered Meshes
Stefano Esposito, Anpei Chen, Christian Reiser +7
High-quality view synthesis relies on volume rendering, splatting, or surface rendering. While surface rendering is typically the fastest, it struggles to accurately model fuzzy ge…
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…
ConsistDreamer: 3D-Consistent 2D Diffusion for High-Fidelity Scene Editing
Jun-Kun Chen, Samuel Rota Bulò, Norman Müller +3
This paper proposes ConsistDreamer - a novel framework that lifts 2D diffusion models with 3D awareness and 3D consistency, thus enabling high-fidelity instruction-guided scene edi…
Dynamic 3D Gaussian Fields for Urban Areas
Tobias Fischer, Jonas Kulhanek, Samuel Rota Bulò +3
We present an efficient neural 3D scene representation for novel-view synthesis (NVS) in large-scale, dynamic urban areas. Existing works are not well suited for applications like…
Revising Densification in Gaussian Splatting
Samuel Rota Bulò, Lorenzo Porzi, Peter Kontschieder
In this paper, we address the limitations of Adaptive Density Control (ADC) in 3D Gaussian Splatting (3DGS), a scene representation method achieving high-quality, photorealistic re…
Robust Gaussian Splatting
François Darmon, Lorenzo Porzi, Samuel Rota-Bulò +1
In this paper, we address common error sources for 3D Gaussian Splatting (3DGS) including blur, imperfect camera poses, and color inconsistencies, with the goal of improving its ro…
Multi-Level Neural Scene Graphs for Dynamic Urban Environments
Tobias Fischer, Lorenzo Porzi, Samuel Rota Bulò +2
We estimate the radiance field of large-scale dynamic areas from multiple vehicle captures under varying environmental conditions. Previous works in this domain are either restrict…
HybridNeRF: Efficient Neural Rendering via Adaptive Volumetric Surfaces
Haithem Turki, Vasu Agrawal, Samuel Rota Bulò +5
Neural radiance fields provide state-of-the-art view synthesis quality but tend to be slow to render. One reason is that they make use of volume rendering, thus requiring many samp…
VR-NeRF: High-Fidelity Virtualized Walkable Spaces
Linning Xu, Vasu Agrawal, William Laney +10
We present an end-to-end system for the high-fidelity capture, model reconstruction, and real-time rendering of walkable spaces in virtual reality using neural radiance fields. To…
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…
OrienterNet: Visual Localization in 2D Public Maps with Neural Matching
Paul-Edouard Sarlin, Daniel DeTone, Tsun-Yi Yang +7
Humans can orient themselves in their 3D environments using simple 2D maps. Differently, algorithms for visual localization mostly rely on complex 3D point clouds that are expensiv…
Panoptic Lifting for 3D Scene Understanding with Neural Fields
Yawar Siddiqui, Lorenzo Porzi, Samuel Rota Buló +4
We propose Panoptic Lifting, a novel approach for learning panoptic 3D volumetric representations from images of in-the-wild scenes. Once trained, our model can render color images…