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In recent years, the usefulness of 3D shape estimation is being realized in microscopic or close-range imaging, as the 3D information can further be used in various applications. Due to limited depth of field at such small distances, the…

Computer Vision and Pattern Recognition · Computer Science 2017-01-02 Arnav Bhavsar

Learning to model and reconstruct humans in clothing is challenging due to articulation, non-rigid deformation, and varying clothing types and topologies. To enable learning, the choice of representation is the key. Recent work uses neural…

Computer Vision and Pattern Recognition · Computer Science 2021-04-16 Qianli Ma , Shunsuke Saito , Jinlong Yang , Siyu Tang , Michael J. Black

Accurate modelling of object deformations is crucial for a wide range of robotic manipulation tasks, where interacting with soft or deformable objects is essential. Current methods struggle to generalise to unseen forces or adapt to new…

Robotics · Computer Science 2025-05-20 Sean M. V. Collins , Brendan Tidd , Mahsa Baktashmotlagh , Peyman Moghadam

In many image analysis problems, the contours of objects carry important statistical information about shape. Such contours are typically affected by deformation variables including scaling, translation, rotation, and reparametrization.…

Methodology · Statistics 2026-05-26 Issam-Ali Moindjié , Cédric Beaulac , Marie-Hélène Descary

We present a new deep learning approach for matching deformable shapes by introducing {\it Shape Deformation Networks} which jointly encode 3D shapes and correspondences. This is achieved by factoring the surface representation into (i) a…

Computer Vision and Pattern Recognition · Computer Science 2018-07-30 Thibault Groueix , Matthew Fisher , Vladimir G. Kim , Bryan C. Russell , Mathieu Aubry

In this document we study some local deformation properties of matrix representations of the universal C$^*$-algebras denoted by $\mathbb{I}^{m}_\varepsilon[p_1,\ldots,p_m]$ and $\mathbb{S}^{m-1}_\varepsilon[p_1,\ldots,p_m]$, and that we…

Operator Algebras · Mathematics 2016-08-31 Fredy Vides

Recent deep learning-based methods have shown promising results and runtime advantages in deformable image registration. However, analyzing the effects of hyperparameters and searching for optimal regularization parameters prove to be too…

Computer Vision and Pattern Recognition · Computer Science 2021-07-06 Tony C. W. Mok , Albert C. S. Chung

High-quality reconstruction of controllable 3D head avatars from 2D videos is highly desirable for virtual human applications in movies, games, and telepresence. Neural implicit fields provide a powerful representation to model 3D head…

Computer Vision and Pattern Recognition · Computer Science 2023-04-24 Chuhan Chen , Matthew O'Toole , Gaurav Bharaj , Pablo Garrido

Implicit 3D surface reconstruction of an object from its partial and noisy 3D point cloud scan is the classical geometry processing and 3D computer vision problem. In the literature, various 3D shape representations have been developed,…

Computer Vision and Pattern Recognition · Computer Science 2024-02-13 Atharva Pandey , Vishal Yadav , Rajendra Nagar , Santanu Chaudhury

In this paper, a feature extraction approach for the deformable linear object is presented, which uses a Bezier curve to represent the original geometric shape. The proposed extraction strategy is combined with a parameterization technique,…

Robotics · Computer Science 2023-12-29 Fangqing Chen

Real-world time series data are often generated from several sources of variation. Learning representations that capture the factors contributing to this variability enables a better understanding of the data via its underlying generative…

Machine Learning · Computer Science 2022-02-14 Sana Tonekaboni , Chun-Liang Li , Sercan Arik , Anna Goldenberg , Tomas Pfister

Facial recognition systems have achieved remarkable success by leveraging deep neural networks, advanced loss functions, and large-scale datasets. However, their performance often deteriorates in real-world scenarios involving low-quality…

Computer Vision and Pattern Recognition · Computer Science 2025-10-29 Sadaf Gulshad , Abdullah Aldahlawi

Knowledge of shape geometry plays a pivotal role in many shape analysis applications. In this paper we introduce a local geometry-inclusive global representation of 3D shapes based on computation of the shortest quasi-geodesic paths between…

Computer Vision and Pattern Recognition · Computer Science 2017-07-24 Somenath Das , Suchendra M. Bhandarkar

Reconstructing 3D human heads in low-view settings presents technical challenges, mainly due to the pronounced risk of overfitting with limited views and high-frequency signals. To address this, we propose geometry decomposition and adopt a…

Computer Vision and Pattern Recognition · Computer Science 2023-08-21 Baixin Xu , Jiarui Zhang , Kwan-Yee Lin , Chen Qian , Ying He

We propose a functional view of matrix decomposition problems on graphs such as geometric matrix completion and graph regularized dimensionality reduction. Our unifying framework is based on the key idea that using a reduced basis to…

Machine Learning · Computer Science 2021-02-08 Abhishek Sharma , Maks Ovsjanikov

3D shape editing is widely used in a range of applications such as movie production, computer games and computer aided design. It is also a popular research topic in computer graphics and computer vision. In past decades, researchers have…

Graphics · Computer Science 2021-03-03 Yu-Jie Yuan , Yu-Kun Lai , Tong Wu , Lin Gao , Ligang Liu

The goal of this paper is to take a single 2D image of a scene and recover the 3D structure in terms of a small set of factors: a layout representing the enclosing surfaces as well as a set of objects represented in terms of shape and pose.…

Computer Vision and Pattern Recognition · Computer Science 2018-04-25 Shubham Tulsiani , Saurabh Gupta , David Fouhey , Alexei A. Efros , Jitendra Malik

The free-form deformation model can represent a wide range of non-rigid deformations by manipulating a control point lattice over the image. However, due to a large number of parameters, it is challenging to fit the free-form deformation…

Computer Vision and Pattern Recognition · Computer Science 2022-06-10 Takumi Nakane , Haoran Xie , Chao Zhang

In current biological and medical research, statistical shape modeling (SSM) provides an essential framework for the characterization of anatomy/morphology. Such analysis is often driven by the identification of a relatively small number of…

Computer Vision and Pattern Recognition · Computer Science 2021-11-16 Riddhish Bhalodia , Shireen Elhabian , Ladislav Kavan , Ross Whitaker

Estimating graphical model structure from high-dimensional and undersampled data is a fundamental problem in many scientific fields. Existing approaches, such as GLASSO, latent variable GLASSO, and latent tree models, suffer from high…

Machine Learning · Statistics 2019-09-18 Greg Ver Steeg , Hrayr Harutyunyan , Daniel Moyer , Aram Galstyan