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Related papers: Scan2Mesh: From Unstructured Range Scans to 3D Mes…

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Mesh is an important and powerful type of data for 3D shapes and widely studied in the field of computer vision and computer graphics. Regarding the task of 3D shape representation, there have been extensive research efforts concentrating…

Computer Vision and Pattern Recognition · Computer Science 2018-11-29 Yutong Feng , Yifan Feng , Haoxuan You , Xibin Zhao , Yue Gao

Polygon meshes are an efficient representation of 3D geometry, and are of central importance in computer graphics, robotics and games development. Existing learning-based approaches have avoided the challenges of working with 3D meshes,…

Graphics · Computer Science 2020-02-26 Charlie Nash , Yaroslav Ganin , S. M. Ali Eslami , Peter W. Battaglia

We present a generative model to synthesize 3D shapes as sets of handles -- lightweight proxies that approximate the original 3D shape -- for applications in interactive editing, shape parsing, and building compact 3D representations. Our…

Computer Vision and Pattern Recognition · Computer Science 2020-04-08 Matheus Gadelha , Giorgio Gori , Duygu Ceylan , Radomir Mech , Nathan Carr , Tamy Boubekeur , Rui Wang , Subhransu Maji

In this work, we introduce Unique3D, a novel image-to-3D framework for efficiently generating high-quality 3D meshes from single-view images, featuring state-of-the-art generation fidelity and strong generalizability. Previous methods based…

Computer Vision and Pattern Recognition · Computer Science 2024-10-29 Kailu Wu , Fangfu Liu , Zhihan Cai , Runjie Yan , Hanyang Wang , Yating Hu , Yueqi Duan , Kaisheng Ma

Controllable, high-fidelity mesh editing remains a significant challenge in 3D content creation. Existing generative methods often struggle with complex geometries and fail to produce detailed results. We propose CraftMesh, a novel…

Graphics · Computer Science 2026-03-31 James Jincheng , Yuxiao Wu , Youcheng Cai , Ligang Liu

We introduce X-Ray, a novel 3D sequential representation inspired by the penetrability of x-ray scans. X-Ray transforms a 3D object into a series of surface frames at different layers, making it suitable for generating 3D models from…

Computer Vision and Pattern Recognition · Computer Science 2024-06-04 Tao Hu , Wenhang Ge , Yuyang Zhao , Gim Hee Lee

We present a method for creating 3D indoor scenes with a generative model learned from a collection of semantic-segmented depth images captured from different unknown scenes. Given a room with a specified size, our method automatically…

Computer Vision and Pattern Recognition · Computer Science 2021-08-23 Ming-Jia Yang , Yu-Xiao Guo , Bin Zhou , Xin Tong

We are interested in reconstructing the mesh representation of object surfaces from point clouds. Surface reconstruction is a prerequisite for downstream applications such as rendering, collision avoidance for planning, animation, etc.…

Computer Vision and Pattern Recognition · Computer Science 2020-10-01 Minghua Liu , Xiaoshuai Zhang , Hao Su

Recent progress in image and video synthesis has inspired their use in advancing 3D scene generation. However, we observe that text-to-image and -video approaches struggle to maintain scene- and object-level consistency beyond a limited…

Computer Vision and Pattern Recognition · Computer Science 2026-03-26 Manuel-Andreas Schneider , Angela Dai

Sketch-based modeling strives to bring the ease and immediacy of drawing to the 3D world. However, while drawings are easy for humans to create, they are very challenging for computers to interpret due to their sparsity and ambiguity. We…

Graphics · Computer Science 2018-06-20 Johanna Delanoy , Mathieu Aubry , Phillip Isola , Alexei A. Efros , Adrien Bousseau

Recent advances in 3D vision have led to specialized models for either 3D understanding (e.g., shape classification, segmentation, reconstruction) or 3D generation (e.g., synthesis, completion, and editing). However, these tasks are often…

Computer Vision and Pattern Recognition · Computer Science 2026-04-21 Peng Huang , Yifeng Chen , Zeyu Zhang , Hao Tang

For embodied agents to infer representations of the underlying 3D physical world they inhabit, they should efficiently combine multisensory cues from numerous trials, e.g., by looking at and touching objects. Despite its importance,…

Machine Learning · Computer Science 2019-11-11 Jae Hyun Lim , Pedro O. Pinheiro , Negar Rostamzadeh , Christopher Pal , Sungjin Ahn

In this work, we propose an automatic mesh generation algorithm, FlowMesher, which can be used to generate unstructured meshes for mesh domains in any shape with minimum (or even no) user intervention. The approach can generate high-quality…

Graphics · Computer Science 2021-03-11 Zhujiang Wang , Arun R. Srinivasa , J. N. Reddy , Adam Dubrowski

Generative Neural Radiance Field (GNeRF) models, which extract implicit 3D representations from 2D images, have recently been shown to produce realistic images representing rigid/semi-rigid objects, such as human faces or cars. However,…

Computer Vision and Pattern Recognition · Computer Science 2022-07-19 Jichao Zhang , Enver Sangineto , Hao Tang , Aliaksandr Siarohin , Zhun Zhong , Nicu Sebe , Wei Wang

Many methods have been proposed over the years to tackle the task of facial 3D geometry and texture recovery from a single image. Such methods often fail to provide high-fidelity texture without relying on 3D facial scans during training.…

Computer Vision and Pattern Recognition · Computer Science 2021-10-12 Ron Slossberg , Ibrahim Jubran , Ron Kimmel

Rendering is the process of generating 2D images from 3D assets, simulated in a virtual environment, typically with a graphics pipeline. By inverting such renderer, one can think of a learning approach to predict a 3D shape from an input…

Computer Vision and Pattern Recognition · Computer Science 2019-01-24 Shichen Liu , Weikai Chen , Tianye Li , Hao Li

Traditional 3D face models learn a latent representation of faces using linear subspaces from limited scans of a single database. The main roadblock of building a large-scale face model from diverse 3D databases lies in the lack of dense…

Computer Vision and Pattern Recognition · Computer Science 2019-08-15 Feng Liu , Luan Tran , Xiaoming Liu

Recently, multiple formulations of vision problems as probabilistic inversions of generative models based on computer graphics have been proposed. However, applications to 3D perception from natural images have focused on low-dimensional…

Computer Vision and Pattern Recognition · Computer Science 2014-07-08 Tejas D. Kulkarni , Vikash K. Mansinghka , Pushmeet Kohli , Joshua B. Tenenbaum

Normal map is an important and efficient way to represent complex 3D models. A designer may benefit from the auto-generation of high quality and accurate normal maps from freehand sketches in 3D content creation. This paper proposes a deep…

Computer Vision and Pattern Recognition · Computer Science 2021-04-26 Yi He , Haoran Xie , Chao Zhang , Xi Yang , Kazunori Miyata

In this paper, we define and study a new Cloth2Body problem which has a goal of generating 3D human body meshes from a 2D clothing image. Unlike the existing human mesh recovery problem, Cloth2Body needs to address new and emerging…

Computer Vision and Pattern Recognition · Computer Science 2023-09-29 Lu Dai , Liqian Ma , Shenhan Qian , Hao Liu , Ziwei Liu , Hui Xiong
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