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Related papers: On Smooth 3D Frame Field Design

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This paper addresses constrained smooth saddle-point problems in settings where projection onto the feasible sets is computationally expensive. We bridge the gap between projection-based and projection-free optimization by introducing a…

Optimization and Control · Mathematics 2026-04-02 Khanh-Hung Giang-Tran , Soroosh Shafiee , Nam Ho-Nguyen

We present a method to simulate fluid flow on evolving surfaces, e.g., an oil film on a water surface. Given an animated surface (e.g., extracted from a particle-based fluid simulation) in three-dimensional space, we add a second simulation…

Graphics · Computer Science 2020-10-08 Dieter Morgenroth , Stefan Reinhardt , Daniel Weiskopf , Bernhard Eberhardt

We present a method for generating orthogonal quadrilateral meshes subject to user-defined feature alignment and sizing constraints. The approach relies on computing integrable orthogonal frame fields, whose symmetries are implicitly…

Computational Geometry · Computer Science 2026-04-07 Mattéo Couplet , Alexandre Chemin , David Bommes , Edward Chien

The great flexibility of a view camera allows to take high quality photographs that would not be possible any other way. But making a given object into focus is a long and tedious task, although the underlying laws are well known. This…

Optimization and Control · Mathematics 2015-03-18 Stéphane Mottelet , Luc de Saint Germain , Olivier Mondin

This paper introduces a generalised 3rd-order Spectral Representation Method for the simulation of multi-dimensional stochastic fields with asymmetric non-linearities. The simulated random fields satisfy a prescribed Power Spectrum and…

Statistics Theory · Mathematics 2020-07-06 Lohit Vandanapu , Michael D. Shields

We present a framework to train a structured prediction model by performing smoothing on the inference algorithm it builds upon. Smoothing overcomes the non-smoothness inherent to the maximum margin structured prediction objective, and…

Machine Learning · Statistics 2019-02-11 Krishna Pillutla , Vincent Roulet , Sham M. Kakade , Zaid Harchaoui

With the rapid development of high-resolution 3D vision applications, the traditional way of manipulating surface detail requires considerable memory and computing time. To address these problems, we introduce an efficient surface detail…

Computer Vision and Pattern Recognition · Computer Science 2023-07-18 Wuyuan Xie , Miaohui Wang , Di Lin , Boxin Shi , Jianmin Jiang

Differentiable rendering is an essential operation in modern vision, allowing inverse graphics approaches to 3D understanding to be utilized in modern machine learning frameworks. Explicit shape representations (voxels, point clouds, or…

Computer Vision and Pattern Recognition · Computer Science 2021-12-13 Tristan Aumentado-Armstrong , Stavros Tsogkas , Sven Dickinson , Allan Jepson

Recent advances in 3D Gaussian representations have significantly improved the quality and efficiency of image-based scene reconstruction. Their explicit nature facilitates real-time rendering and fast optimization, yet extracting accurate…

In this paper, we tackle the challenging problem of 3D keypoint estimation of general objects using a novel implicit representation. Previous works have demonstrated promising results for keypoint prediction through direct coordinate…

Computer Vision and Pattern Recognition · Computer Science 2023-06-21 Xiangyu Zhu , Dong Du , Haibin Huang , Chongyang Ma , Xiaoguang Han

We study the problem of moving a vertex in an unstructured mesh of triangular, quadrilateral, or tetrahedral elements to optimize the shapes of adjacent elements. We show that many such problems can be solved in linear time using…

Computational Geometry · Computer Science 2010-01-21 Nina Amenta , Marshall Bern , David Eppstein

We consider the unconstrained optimization problem whose objective function is composed of a smooth and a non-smooth conponents where the smooth component is the expectation a random function. This type of problem arises in some interesting…

Optimization and Control · Mathematics 2011-07-01 Qihang Lin , Xi Chen , Javier Pena

Existing 3D surface representation approaches are unable to accurately classify pixels and their orientation lying on the boundary of an object. Thus resulting in coarse representations which usually require post-processing steps to extract…

Computer Vision and Pattern Recognition · Computer Science 2019-01-23 Mateusz Michalkiewicz , Jhony K. Pontes , Dominic Jack , Mahsa Baktashmotlagh , Anders Eriksson

We present a unified framework tackling two problems: class-specific 3D reconstruction from a single image, and generation of new 3D shape samples. These tasks have received considerable attention recently; however, existing approaches rely…

Computer Vision and Pattern Recognition · Computer Science 2018-11-16 Paul Henderson , Vittorio Ferrari

This paper studies the mismatch removal problem, which may serve as the subsequent step of feature matching. Non-rigid deformation makes it difficult to remove mismatches because no parametric transformation can be found. To solve this…

Computer Vision and Pattern Recognition · Computer Science 2020-07-20 Haoyin Zhou , Jagadeesan Jayender

In this paper, we study the problem of 3D scene geometry decomposition and manipulation from 2D views. By leveraging the recent implicit neural representation techniques, particularly the appealing neural radiance fields, we introduce an…

Computer Vision and Pattern Recognition · Computer Science 2023-03-13 Bing Wang , Lu Chen , Bo Yang

We propose a new methodology to estimate the 3D displacement field of deformable objects from video sequences using standard monocular cameras. We solve in real time the complete (possibly visco-)hyperelasticity problem to properly describe…

Computer Vision and Pattern Recognition · Computer Science 2021-10-14 Alberto Badias , Iciar Alfaro , David Gonzalez , Francisco Chinesta , Elias Cueto

In this work we present a novel approach for computing correspondences between non-rigid objects, by exploiting a reduced representation of deformation fields. Different from existing works that represent deformation fields by training a…

Computer Vision and Pattern Recognition · Computer Science 2022-11-29 Ramana Sundararaman , Riccardo Marin , Emanuele Rodola , Maks Ovsjanikov

In this work, we present an efficient optic flow algorithm for the extraction of vertically resolved 3D atmospheric motion vector (AMV) fields from incomplete hyperspectral image data measures by infrared sounders. The model at the heart of…

Computer Vision and Pattern Recognition · Computer Science 2023-10-26 P. Héas , O. Hautecoeur , R. Borde

Smooth parametrization consists in a subdivision of the mathematical objects under consideration into simple pieces, and then parametric representation of each piece, while keeping control of high order derivatives. The main goal of the…

Computational Geometry · Computer Science 2014-07-14 Y. Yomdin