9 papers
Guiding Image-to-3D Generation with Test-Time Partial Observations
Jerred Chen, Simon Weber, Ronald Clark
Image-to-3D models can generate visually compelling 3D assets from a single RGB image, but their geometry is often only loosely constrained by the available observations, limiting…
Initialization-Free Bundle Adjustment Revisited: A Controlled Experimental Study
Simon Weber, Mateo de Mayo, Je Hyeong Hong +3
Initialization-free bundle adjustment (InitFree BA) aims to recover camera poses and scene structure directly from image observations, avoiding the geometric initialization stages…
Functional Attention: From Pairwise Affinities to Functional Correspondences
Jiefang Xiao, Maolin Gao, Simon Weber +2
Learning mappings between infinite-dimensional function spaces, or operator learning, is essential for many machine learning applications. Although transformer-based operators are…
Harnessing Data Asymmetry: Manifold Learning in the Finsler World
Thomas Dagès, Simon Weber, Daniel Cremers +1
Manifold learning is a fundamental task at the core of data analysis and visualisation. It aims to capture the simple underlying structure of complex high-dimensional data by prese…
Finsler Multi-Dimensional Scaling: Manifold Learning for Asymmetric Dimensionality Reduction and Embedding
Thomas Dagès, Simon Weber, Ya-Wei Eileen Lin +5
Dimensionality reduction is a fundamental task that aims to simplify complex data by reducing its feature dimensionality while preserving essential patterns, with core applications…
Power Variable Projection for Initialization-Free Large-Scale Bundle Adjustment
Simon Weber, Je Hyeong Hong, Daniel Cremers
Most Bundle Adjustment (BA) solvers like the Levenberg-Marquardt algorithm require a good initialization. Instead, initialization-free BA remains a largely uncharted territory. The…
Flattening the Parent Bias: Hierarchical Semantic Segmentation in the Poincaré Ball
Simon Weber, Barış Zöngür, Nikita Araslanov +1
Hierarchy is a natural representation of semantic taxonomies, including the ones routinely used in image segmentation. Indeed, recent work on semantic segmentation reports improved…
Finsler-Laplace-Beltrami Operators with Application to Shape Analysis
Simon Weber, Thomas Dagès, Maolin Gao +1
The Laplace-Beltrami operator (LBO) emerges from studying manifolds equipped with a Riemannian metric. It is often called the Swiss army knife of geometry processing as it allows t…
Multidirectional Conjugate Gradients for Scalable Bundle Adjustment
Simon Weber, Nikolaus Demmel, Daniel Cremers
We revisit the problem of large-scale bundle adjustment and propose a technique called Multidirectional Conjugate Gradients that accelerates the solution of the normal equation by…