56 citations · 308 across the 70 of their papers we have counts for
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Task-Induced Riemannian Metrics for Vision Transformer Feature Spaces
Andrew Bond, Ege Erdem Özlü, Tuna Çimen +4
Methods operating on Vision Transformer (ViT) feature spaces typically rely on Euclidean distance or cosine similarity. This assumes that every direction is equally meaningful, but…
Heat Kernel Textures: the Geodesic Gaussians That Do Not Splat
Simone Foti, Caner Korkmaz, Stefanos Zafeiriou +1
3D Gaussian Splatting has recently revolutionised novel view synthesis as well as many other 3D vision methods and applications. Drawing inspiration from this representation, we no…
Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models
Lisa Weijler, Irene Ballester, Guofeng Mei +2
Geometric foundation models, such as the Visual Geometry Grounded Transformer (VGGT), provide strong 3D priors from unposed images. However, such models operate purely in a feed-fo…
SAMoR: Motion Modelling for Articulated Objects of Any Skeleton and Topology
Yuhao Zhang, Gerard Pons-Moll, Tolga Birdal
Modeling motion for articulated objects of arbitrary skeleton topology remains difficult: existing motion generators target a fixed human skeleton, and prior adaptations either fai…
DisPOSE: Projected Polystochastic Diffusion for Self-Supervised Multi-View 3D Human Pose Estimation
Tony Danjun Wang, Tolga Birdal, Nassir Navab +1
Recovering 3D human poses for multiple individuals from different camera views is a fundamental bottleneck for analyzing interacting behaviors. Existing self-supervised approaches…
Parallelised Differentiable Straightest Geodesics for 3D Meshes
Hippolyte Verninas, Caner Korkmaz, Stefanos Zafeiriou +2
Machine learning has been progressively generalised to operate within non-Euclidean domains, but geometrically accurate methods for learning on surfaces are still falling behind. T…
TopoOR: A Unified Topological Scene Representation for the Operating Room
Tony Danjun Wang, Ka Young Kim, Tolga Birdal +2
Surgical Scene Graphs abstract the complexity of surgical operating rooms (OR) into a structure of entities and their relations, but existing paradigms suffer from strictly dyadic…
COMPOSE: Hypergraph Cover Optimization for Multi-view 3D Human Pose Estimation
Tony Danjun Wang, Tolga Birdal, Nassir Navab +1
3D human pose estimation from sparse multi-view camera rigs is an essential task for numerous applications, including action recognition, sports analysis, and human-robot interacti…
MoLingo: Motion-Language Alignment for Text-to-Human Motion Generation
Yannan He, Garvita Tiwari, Xiaohan Zhang +4
We introduce MoLingo, a text-to-motion (T2M) model that generates realistic, lifelike human motion by denoising in a continuous latent space. Recent works perform latent space diff…
CuMPerLay: Learning Cubical Multiparameter Persistence Vectorizations
Caner Korkmaz, Brighton Nuwagira, Barış Coşkunuzer +1
We present CuMPerLay, a novel differentiable vectorization layer that enables the integration of Cubical Multiparameter Persistence (CMP) into deep learning pipelines. While CMP pr…
Quantum-enhanced Computer Vision: Going Beyond Classical Algorithms
Natacha Kuete Meli, Shuteng Wang, Marcel Seelbach Benkner +5
Quantum-enhanced Computer Vision (QeCV) is a new research field at the intersection of computer vision, optimisation theory, machine learning and quantum computing. It has high pot…
Geometric Neural Distance Fields for Learning Human Motion Priors
Zhengdi Yu, Simone Foti, Linguang Zhang +4
We introduce Neural Riemannian Motion Fields (NRMF), a novel 3D generative human motion prior that enables robust, temporally consistent, and physically plausible 3D motion recover…
Forecasting Continuous Non-Conservative Dynamical Systems in SO(3)
Lennart Bastian, Mohammad Rashed, Nassir Navab +1
Modeling the rotation of moving objects is a fundamental task in computer vision, yet extrapolation still presents numerous challenges: (1) unknown quantities such as the m…
Continuous-Time SO(3) Forecasting with Savitzky--Golay Neural Controlled Differential Equations
Lennart Bastian, Mohammad Rashed, Nassir Navab +1
Tracking and forecasting the rotation of objects is fundamental in computer vision and robotics, yet SO(3) extrapolation remains challenging as (1) sensor observations can be noisy…
Towards Dynamic 3D Reconstruction of Hand-Instrument Interaction in Ophthalmic Surgery
Ming Hu, Zhengdi Yu, Feilong Tang +7
Accurate 3D reconstruction of hands and instruments is critical for vision-based analysis of ophthalmic microsurgery, yet progress has been hampered by the lack of realistic, large…
A Flag Decomposition for Hierarchical Datasets
Nathan Mankovich, Ignacio Santamaria, Gustau Camps-Valls +1
Flag manifolds encode nested sequences of subspaces and serve as powerful structures for various computer vision and machine learning applications. Despite their utility in tasks s…
Dyn-HaMR: Recovering 4D Interacting Hand Motion from a Dynamic Camera
Zhengdi Yu, Stefanos Zafeiriou, Tolga Birdal
We propose Dyn-HaMR, to the best of our knowledge, the first approach to reconstruct 4D global hand motion from monocular videos recorded by dynamic cameras in the wild. Reconstruc…
Alignist: CAD-Informed Orientation Distribution Estimation by Fusing Shape and Correspondences
Shishir Reddy Vutukur, Rasmus Laurvig Haugaard, Junwen Huang +2
Object pose distribution estimation is crucial in robotics for better path planning and handling of symmetric objects. Recent distribution estimation approaches employ contrastive…
UV-free Texture Generation with Denoising and Geodesic Heat Diffusions
Simone Foti, Stefanos Zafeiriou, Tolga Birdal
Seams, distortions, wasted UV space, vertex-duplication, and varying resolution over the surface are the most prominent issues of the standard UV-based texturing of meshes. These i…
NeRF-Feat: 6D Object Pose Estimation using Feature Rendering
Shishir Reddy Vutukur, Heike Brock, Benjamin Busam +3
Object Pose Estimation is a crucial component in robotic grasping and augmented reality. Learning based approaches typically require training data from a highly accurate CAD model…
HyperSDFusion: Bridging Hierarchical Structures in Language and Geometry for Enhanced 3D Text2Shape Generation
Zhiying Leng, Tolga Birdal, Xiaohui Liang +1
3D shape generation from text is a fundamental task in 3D representation learning. The text-shape pairs exhibit a hierarchical structure, where a general text like ``chair" covers…
NRDF: Neural Riemannian Distance Fields for Learning Articulated Pose Priors
Yannan He, Garvita Tiwari, Tolga Birdal +2
Faithfully modeling the space of articulations is a crucial task that allows recovery and generation of realistic poses, and remains a notorious challenge. To this end, we introduc…
SignAvatars: A Large-scale 3D Sign Language Holistic Motion Dataset and Benchmark
Zhengdi Yu, Shaoli Huang, Yongkang Cheng +1
We present SignAvatars, the first large-scale, multi-prompt 3D sign language (SL) motion dataset designed to bridge the communication gap for Deaf and hard-of-hearing individuals.…
Projected Stochastic Gradient Descent with Quantum Annealed Binary Gradients
Maximilian Krahn, Michele Sasdelli, Fengyi Yang +4
We present, QP-SBGD, a novel layer-wise stochastic optimiser tailored towards training neural networks with binary weights, known as binary neural networks (BNNs), on quantum hardw…