2 citations · 5 across the 12 of their papers we have counts for
14 papers
Teaching DINOv3 About Partial 3D Geometry: A Self-Supervised Geometry-Aware Approach
Viktoria Ehm, Dongliang Cao, Riccardo Marin +4
Partial shape matching is a crucial yet underexplored problem in 3D vision, with significant relevance to real-world scenarios where shapes are often only partially observed. Exist…
Ordered Diffusion for 3D Human Registration
Mattia Masiero, Ilya A. Petrov, Daniel Cremers +2
3D human registration has historically been treated as a regression task, assuming a unique ground-truth alignment exists between the template and an input point cloud. In reality,…
DeepShapeMatchingKit: Accelerated Functional Map Solver and Shape Matching Pipelines Revisited
Yizheng Xie, Lennart Bastian, Congyue Deng +3
Deep functional maps, leveraging learned feature extractors and spectral correspondence solvers, are fundamental to non-rigid 3D shape matching. Based on an analysis of open-source…
An Integer Linear Programming Approach to Geometrically Consistent Partial-Partial Shape Matching
Viktoria Ehm, Paul Roetzer, Florian Bernard +1
The task of establishing correspondences between two 3D shapes is a long-standing challenge in computer vision. While numerous studies address full-full and partial-full 3D shape m…
PRaDA: Projective Radial Distortion Averaging
Daniil Sinitsyn, Linus Härenstam-Nielsen, Daniel Cremers
We tackle the problem of automatic calibration of radially distorted cameras in challenging conditions. Accurately determining distortion parameters typically requires either 1) so…
TwoSquared: 4D Generation from 2D Image Pairs
Lu Sang, Zehranaz Canfes, Dongliang Cao +3
Despite the astonishing progress in generative AI, 4D dynamic object generation remains an open challenge. With limited high-quality training data and heavy computing requirements,…
PRISM: Probabilistic Representation for Integrated Shape Modeling and Generation
Lei Cheng, Mahdi Saleh, Qing Cheng +4
Despite the advancements in 3D full-shape generation, accurately modeling complex geometries and semantics of shape parts remains a significant challenge, particularly for shapes w…
Semantic Library Adaptation: LoRA Retrieval and Fusion for Open-Vocabulary Semantic Segmentation
Reza Qorbani, Gianluca Villani, Theodoros Panagiotakopoulos +8
Open-vocabulary semantic segmentation models associate vision and text to label pixels from an undefined set of classes using textual queries, providing versatile performance on no…
4Deform: Neural Surface Deformation for Robust Shape Interpolation
Lu Sang, Zehranaz Canfes, Dongliang Cao +3
Generating realistic intermediate shapes between non-rigidly deformed shapes is a challenging task in computer vision, especially with unstructured data (e.g., point clouds) where…
Implicit Neural Surface Deformation with Explicit Velocity Fields
Lu Sang, Zehranaz Canfes, Dongliang Cao +2
In this work, we introduce the first unsupervised method that simultaneously predicts time-varying neural implicit surfaces and deformations between pairs of point clouds. We propo…
Beyond Complete Shapes: A Benchmark for Quantitative Evaluation of 3D Shape Surface Matching Algorithms
Viktoria Ehm, Nafie El Amrani, Yizheng Xie +9
Finding correspondences between 3D deformable shapes is an important and long-standing problem in geometry processing, computer vision, graphics, and beyond. While various shape ma…
DiffCD: A Symmetric Differentiable Chamfer Distance for Neural Implicit Surface Fitting
Linus Härenstam-Nielsen, Lu Sang, Abhishek Saroha +2
Neural implicit surfaces can be used to recover accurate 3D geometry from imperfect point clouds. In this work, we show that state-of-the-art techniques work by minimizing an appro…
Coloring the Past: Neural Historical Buildings Reconstruction from Archival Photography
David Komorowicz, Lu Sang, Ferdinand Maiwald +1
Historical buildings are a treasure and milestone of human cultural heritage. Reconstructing the 3D models of these building hold significant value. The rapid development of neural…
Erasing the Ephemeral: Joint Camera Refinement and Transient Object Removal for Street View Synthesis
Mreenav Shyam Deka, Lu Sang, Daniel Cremers
Synthesizing novel views for urban environments is crucial for tasks like autonomous driving and virtual tours. Compared to object-level or indoor situations, outdoor settings pres…