activity
20242026
collaborators

12 papers

cs.CV2026

PointDiT: Pixel-Space Diffusion for Monocular Geometry Estimation

Haofei Xu, Rundi Wu, Philipp Henzler +7

State-of-the-art single-image 3D reconstruction methods often rely on complex hybrid architectures and loss functions, or compress geometry into latent spaces in order to leverage…

cs.RO2026

DiskChunGS: Large-Scale 3D Gaussian SLAM Through Chunk-Based Memory Management

Casimir Feldmann, Maximum Wilder-Smith, Vaishakh Patil +4

Recent advances in 3D Gaussian Splatting (3DGS) have demonstrated impressive results for novel view synthesis with real-time rendering capabilities. However, integrating 3DGS with…

cs.CV2026

Good Token Hunting: A Hitchhiker's Guide to Token Selection for Visual Geometry Transformers

Shuhong Zheng, Michael Oechsle, Erik Sandström +3

Visual geometry transformers have become powerful architectures for multi-view 3D reconstruction, enabling joint prediction of multiple 3D attributes in a feed-forward manner. Howe…

cs.CV2026

Stepper: Stepwise Immersive Scene Generation with Multiview Panoramas

Felix Wimbauer, Fabian Manhardt, Michael Oechsle +4

The synthesis of immersive 3D scenes from text is rapidly maturing, driven by novel video generative models and feed-forward 3D reconstruction, with vast potential in AR/VR and wor…

cs.CV2026

AnyUp: Universal Feature Upsampling

Thomas Wimmer, Prune Truong, Marie-Julie Rakotosaona +4

We introduce AnyUp, a method for feature upsampling that can be applied to any vision feature at any resolution, without encoder-specific training. Existing learning-based upsample…

cs.CV2026

MOSAIC-GS: Monocular Scene Reconstruction via Advanced Initialization for Complex Dynamic Environments

Svitlana Morkva, Maximum Wilder-Smith, Michael Oechsle +3

We present MOSAIC-GS, a novel, fully explicit, and computationally efficient approach for high-fidelity dynamic scene reconstruction from monocular videos using Gaussian Splatting.…