Christian Schmidt — accepted AI-conference papers

2026

Block-Sparse Global Attention for Efficient Multi-View Geometry Transformers

Chung-Shien Brian Wang, Christian Schmidt, Jens Piekenbrinck, Bastian Leibe

CVPR 2026

Efficient and accurate feed-forward multi-view reconstruction has long been an important task in computer vision. Recent transformer-based models like VGGT, \pi^3 and MapAnything have demonstrated remarkable performance with relatively simple architectures. However, their scalability is fundamentall

Cited by 0 Source ↗code ↗Scholar ↗

2024

Look Gauss, No Pose: Novel View Synthesis using Gaussian Splatting without Accurate Pose Initialization

Christian Schmidt, Jens Piekenbrinck, Bastian Leibe

IROS 2024poster

3D Gaussian Splatting has recently emerged as a powerful tool for fast and accurate novel-view synthesis from a set of posed input images. However, like most novel-view synthesis approaches, it relies on accurate camera pose information, limiting its applicability in real-world scenarios where acqui…

Cited by 3 Source ↗code ↗Scholar ↗