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Dense point cloud generation from a sparse or incomplete point cloud is a crucial and challenging problem in 3D computer vision and computer graphics. So far, the existing methods are either computationally too expensive, suffer from…

Computer Vision and Pattern Recognition · Computer Science 2024-03-14 Abol Basher , Jani Boutellier

3D reconstruction and simulation, although interrelated, have distinct objectives: reconstruction requires a flexible 3D representation that can adapt to diverse scenes, while simulation needs a structured representation to model motion…

Computer Vision and Pattern Recognition · Computer Science 2024-11-25 Shaojie Ma , Yawei Luo , Wei Yang , Yi Yang

We present a novel approach for generating isotropic surface triangle meshes directly from unoriented 3D point clouds, with the mesh density adapting to the estimated local feature size (LFS). Popular reconstruction pipelines first…

Graphics · Computer Science 2025-04-24 Rao Fu , Kai Hormann , Pierre Alliez

Fluid flow simulation is a highly active area with applications in a wide range of engineering problems and interactive systems. Meshless methods like the Moving Particle Semi-implicit (MPS) are a great alternative to deal efficiently with…

In this paper, we address unsupervised pose-guided person image generation, which is known challenging due to non-rigid deformation. Unlike previous methods learning a rock-hard direct mapping between human bodies, we propose a new pathway…

Computer Vision and Pattern Recognition · Computer Science 2019-04-19 Sijie Song , Wei Zhang , Jiaying Liu , Tao Mei

Reconstructing accurate implicit surface representations from point clouds remains a challenging task, particularly when data is captured using low-quality scanning devices. These point clouds often contain substantial noise, leading to…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 Tengkai Wang , Weihao Li , Ruikai Cui , Shi Qiu , Nick Barnes

This paper tries to address a fundamental question in point cloud self-supervised learning: what is a good signal we should leverage to learn features from point clouds without annotations? To answer that, we introduce a point cloud…

Computer Vision and Pattern Recognition · Computer Science 2023-05-16 Xiaoyu Tian , Haoxi Ran , Yue Wang , Hang Zhao

Computational fluid dynamics (CFD) in many cases requires designing 3D models manually, which is a tedious task that requires specific skills. In this paper, we present a novel method for performing CFD directly on scanned 3D point clouds.…

Particle methods play an important role in computational fluid dynamics, but they are among the most difficult to implement and solve. The most common method is smoothed particle hydrodynamics, which is suitable for problem settings that…

Fluid Dynamics · Physics 2025-08-26 Masato Shibukawa , Naoya Ozaki , Maximilien Berthet

3D Gaussian Splatting (3DGS) has revolutionized fast novel view synthesis, yet its opacity-based formulation makes surface extraction fundamentally difficult. Unlike implicit methods built on Signed Distance Fields or occupancy, 3DGS lacks…

Computer Vision and Pattern Recognition · Computer Science 2026-04-09 Diego Gomez , Antoine Guédon , Nissim Maruani , Bingchen Gong , Maks Ovsjanikov

Accurate high-speed flow simulations of practical interest require numerical methods with high-resolution properties. In this paper, we present an extension and demonstration of the high-accuracy Gradient-based reconstruction and…

Recent advances in 3D deep learning have shown that it is possible to train highly effective deep models for 3D shape generation, directly from 2D images. This is particularly interesting since the availability of 3D models is still limited…

Computer Vision and Pattern Recognition · Computer Science 2019-11-05 Shichen Liu , Shunsuke Saito , Weikai Chen , Hao Li

Meshes are ubiquitous in visual computing and simulation, yet most existing machine learning techniques represent meshes only indirectly, e.g. as the level set of a scalar field or deformation of a template, or as a disordered triangle soup…

Computer Vision and Pattern Recognition · Computer Science 2025-02-12 Tianchang Shen , Zhaoshuo Li , Marc Law , Matan Atzmon , Sanja Fidler , James Lucas , Jun Gao , Nicholas Sharp

In this work, we explore the idea that effective generative models for point clouds under the autoencoding framework must acknowledge the relationship between a continuous surface, a discretized mesh, and a set of points sampled from the…

Machine Learning · Computer Science 2019-12-10 Austin Dill , Chun-Liang Li , Songwei Ge , Eunsu Kang

Many problems in engineering, chemistry and physics require the representation of solutions in complex geometries. In the paper we deal with a problem of unstructured mesh generation for the control volume method. We propose an algorithm…

Computational Geometry · Computer Science 2007-05-23 Leszczynski Jacek , Pluta Sebastian

Surfaces are typically represented as meshes, which can be extracted from volumetric fields via meshing or optimized directly as surface parameterizations. Volumetric representations occupy 3D space and have a large effective receptive…

Graphics · Computer Science 2026-02-03 Ruiqi Zhang , Jiacheng Wu , Jie Chen

Local and global patterns of an object are closely related. Although each part of an object is incomplete, the underlying attributes about the object are shared among all parts, which makes reasoning the whole object from a single part…

Computer Vision and Pattern Recognition · Computer Science 2020-03-31 Yongming Rao , Jiwen Lu , Jie Zhou

Modern 3D engines and graphics pipelines require mesh as a memory-efficient representation, which allows efficient rendering, geometry processing, texture editing, and many other downstream operations. However, it is still highly difficult…

Computer Vision and Pattern Recognition · Computer Science 2025-03-04 Isabella Liu , Hao Su , Xiaolong Wang

Textured meshes significantly enhance the realism and detail of objects by mapping intricate texture details onto the geometric structure of 3D models. This advancement is valuable across various applications, including entertainment,…

Graphics · Computer Science 2024-12-12 Kaiwei Zhang , Dandan Zhu , Xiongkuo Min , Guangtao Zhai

Recent development of neural implicit function has shown tremendous success on high-quality 3D shape reconstruction. However, most works divide the space into inside and outside of the shape, which limits their representing power to…

Computer Vision and Pattern Recognition · Computer Science 2024-04-10 Jianglong Ye , Yuntao Chen , Naiyan Wang , Xiaolong Wang
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