activity
20242026
collaborators

9 papers

cs.CV2026

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 standard optimizers (Adam, SGD). While stable across diverse scenes, standard optimizers are general-purp…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

Textured Gaussians for Enhanced 3D Scene Appearance Modeling

Brian Chao, Hung-Yu Tseng, Lorenzo Porzi +8

3D Gaussian Splatting (3DGS) has recently emerged as a state-of-the-art 3D reconstruction and rendering technique due to its high-quality results and fast training and rendering ti…