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We introduce a novel approach for the reconstruction of tubular shapes from skeletal representations. Our method processes all skeletal points as a whole, eliminating the need for splitting input structure into multiple segments. We…

Computer Vision and Pattern Recognition · Computer Science 2026-04-10 Guoqing Zhang , Yang Li

Triangle meshes remain the most popular data representation for surface geometry. This ubiquitous representation is essentially a hybrid one that decouples continuous vertex locations from the discrete topological triangulation.…

Computer Vision and Pattern Recognition · Computer Science 2021-09-23 Marie-Julie Rakotosaona , Noam Aigerman , Niloy Mitra , Maks Ovsjanikov , Paul Guerrero

Existing single view, 3D face reconstruction methods can produce beautifully detailed 3D results, but typically only for near frontal, unobstructed viewpoints. We describe a system designed to provide detailed 3D reconstructions of faces…

Computer Vision and Pattern Recognition · Computer Science 2018-04-02 Anh Tuan Tran , Tal Hassner , Iacopo Masi , Eran Paz , Yuval Nirkin , Gerard Medioni

Reconstructing 3D representations from 2D inputs is a fundamental task in computer vision and graphics, serving as a cornerstone for understanding and interacting with the physical world. While traditional methods achieve high fidelity,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-16 Weijie Wang , Qihang Cao , Sensen Gao , Donny Y. Chen , Haofei Xu , Wenjing Bian , Songyou Peng , Tat-Jen Cham , Chuanxia Zheng , Andreas Geiger , Jianfei Cai , Jia-Wang Bian , Bohan Zhuang

We present a method to jointly refine the geometry and semantic segmentation of 3D surface meshes. Our method alternates between updating the shape and the semantic labels. In the geometry refinement step, the mesh is deformed with…

Computer Vision and Pattern Recognition · Computer Science 2017-06-27 Maros Blaha , Mathias Rothermel , Martin R. Oswald , Torsten Sattler , Audrey Richard , Jan D. Wegner , Marc Pollefeys , Konrad Schindler

Creating high-fidelity 3D meshes with arbitrary topology, including open surfaces and complex interiors, remains a significant challenge. Existing implicit field methods often require costly and detail-degrading watertight conversion, while…

Computer Vision and Pattern Recognition · Computer Science 2025-03-28 Xianglong He , Zi-Xin Zou , Chia-Hao Chen , Yuan-Chen Guo , Ding Liang , Chun Yuan , Wanli Ouyang , Yan-Pei Cao , Yangguang Li

We present a method for reconstructing triangle meshes from point clouds. Existing learning-based methods for mesh reconstruction mostly generate triangles individually, making it hard to create manifold meshes. We leverage the properties…

Computer Vision and Pattern Recognition · Computer Science 2021-05-07 Marie-Julie Rakotosaona , Paul Guerrero , Noam Aigerman , Niloy Mitra , Maks Ovsjanikov

We present a learning-based approach to reconstruct buildings as 3D polygonal meshes from airborne LiDAR point clouds. What makes 3D building reconstruction from airborne LiDAR hard is the large diversity of building designs and especially…

Computer Vision and Pattern Recognition · Computer Science 2024-07-30 Yujia Liu , Anton Obukhov , Jan Dirk Wegner , Konrad Schindler

Reconstructing a 3D object from a 2D image is a well-researched vision problem, with many kinds of deep learning techniques having been tried. Most commonly, 3D convolutional approaches are used, though previous work has shown…

Computer Vision and Pattern Recognition · Computer Science 2023-02-17 Rohan Agarwal , Wei Zhou , Xiaofeng Wu , Yuhan Li

We address the novel task of jointly reconstructing the 3D shape, texture, and motion of an object from a single motion-blurred image. While previous approaches address the deblurring problem only in the 2D image domain, our proposed…

Computer Vision and Pattern Recognition · Computer Science 2021-10-27 Denys Rozumnyi , Martin R. Oswald , Vittorio Ferrari , Marc Pollefeys

We propose a method to efficiently compute tomographic projections of a 3D volume represented by a linear combination of shifted B-splines. To do so, we propose a ray-tracing algorithm that computes 3D line integrals with arbitrary…

Computer Vision and Pattern Recognition · Computer Science 2025-11-17 Youssef Haouchat , Sepand Kashani , Aleix Boquet-Pujadas , Philippe Thévenaz , Michael Unser

Reconstructing hand-held objects from monocular RGB images is an appealing yet challenging task. In this task, contacts between hands and objects provide important cues for recovering the 3D geometry of the hand-held objects. Though recent…

Computer Vision and Pattern Recognition · Computer Science 2024-01-17 Junxing Hu , Hongwen Zhang , Zerui Chen , Mengcheng Li , Yunlong Wang , Yebin Liu , Zhenan Sun

Estimating the 3D shape of an object from a single or multiple images has gained popularity thanks to the recent breakthroughs powered by deep learning. Most approaches regress the full object shape in a canonical pose, possibly…

Computer Vision and Pattern Recognition · Computer Science 2020-11-19 Riccardo Spezialetti , David Joseph Tan , Alessio Tonioni , Keisuke Tateno , Federico Tombari

3D face reconstruction plays a very important role in many real-world multimedia applications, including digital entertainment, social media, affection analysis, and person identification. The de-facto pipeline for estimating the parametric…

Computer Vision and Pattern Recognition · Computer Science 2021-01-07 Jialiang Zhang , Lixiang Lin , Jianke Zhu , Steven C. H. Hoi

We propose a new approach for constructing a 3D representation from a 2D wireframe drawing. A drawing is simply a parallel projection of a 3D object onto a 2D surface; humans are able to recreate mental 3D models from 2D representations…

Computer Vision and Pattern Recognition · Computer Science 2010-07-16 Kyle Johnson , Clayton Chang , Hod Lipson

In this research, we address the challenge faced by existing deep learning-based human mesh reconstruction methods in balancing accuracy and computational efficiency. These methods typically prioritize accuracy, resulting in large network…

Computer Vision and Pattern Recognition · Computer Science 2023-02-01 Ayman Ali , Ekkasit Pinyoanuntapong , Pu Wang , Mohsen Dorodchi

For modeling the 3D world behind 2D images, which 3D representation is most appropriate? A polygon mesh is a promising candidate for its compactness and geometric properties. However, it is not straightforward to model a polygon mesh from…

Computer Vision and Pattern Recognition · Computer Science 2017-11-22 Hiroharu Kato , Yoshitaka Ushiku , Tatsuya Harada

Inverse rendering in a 3D format denoted to recovering the 3D properties of a scene given 2D input image(s) and is typically done using 3D Morphable Model (3DMM) based methods from single view images. These models formulate each face as a…

Computer Vision and Pattern Recognition · Computer Science 2017-09-01 Shima Kamyab , Ali Ghodsi , S. Zohreh Azimifar

In the field of data-driven 3D shape analysis and generation, the estimation of global topological features from localized representations such as point clouds, voxels, and neural implicit fields is a longstanding challenge. This paper…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Yihao Luo

Active-stereo-based 3D shape measurement is crucial for various purposes, such as industrial inspection, reverse engineering, and medical systems, due to its strong ability to accurately acquire the shape of textureless objects. Active…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Ryo Furukawa , Kota Nishihara , Hiroshi Kawasaki