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This paper proposes a novel and exact method to reconstruct line-based 3D structure from a single image using Manhattan world assumption. This problem is a distinctly unsolved problem because there can be multiple 3D reconstructions from a…

Computer Vision and Pattern Recognition · Computer Science 2018-10-10 Siddhant Ranade , Srikumar Ramalingam

Recent advancements in 3D perception systems have significantly improved their ability to perform visual recognition tasks such as segmentation. However, these systems still heavily rely on explicit human instruction to identify target…

Computer Vision and Pattern Recognition · Computer Science 2024-04-08 Amrin Kareem , Jean Lahoud , Hisham Cholakkal

Implicit neural fields have made remarkable progress in reconstructing 3D surfaces from multiple images; however, they encounter challenges when it comes to separating individual objects within a scene. Previous work has attempted to tackle…

Computer Vision and Pattern Recognition · Computer Science 2024-07-30 Gemmechu Hassena , Jonathan Moon , Ryan Fujii , Andrew Yuen , Noah Snavely , Steve Marschner , Bharath Hariharan

Scientific imaging techniques such as optical and electron microscopy and computed tomography (CT) scanning are used to study the 3D structure of an object through 2D observations. These observations are related to the original 3D object…

Machine Learning · Computer Science 2019-06-21 Karen Ullrich , Rianne van den Berg , Marcus Brubaker , David Fleet , Max Welling

3D super-resolution (3DSR) aims to reconstruct high-resolution (HR) 3D scenes from low-resolution (LR) multi-view images. Existing methods rely on dense LR inputs and per-scene optimization, which restricts the high-frequency priors for…

Computer Vision and Pattern Recognition · Computer Science 2026-03-02 Xiang Feng , Xiangbo Wang , Tieshi Zhong , Chengkai Wang , Yiting Zhao , Tianxiang Xu , Zhenzhong Kuang , Feiwei Qin , Xuefei Yin , Yanming Zhu

Automated three-dimensional (3D) object reconstruction is the task of building a geometric representation of a physical object by means of sensing its surface. Even though new single view reconstruction techniques can predict the surface,…

Computer Vision and Pattern Recognition · Computer Science 2021-01-27 J. Irving Vasquez-Gomez , David Troncoso , Israel Becerra , Enrique Sucar , Rafael Murrieta-Cid

Inverse problems spanning four or more dimensions such as space, time and other independent parameters have become increasingly important. State-of-the-art 4D reconstruction methods use model based iterative reconstruction (MBIR), but…

Image and Video Processing · Electrical Eng. & Systems 2021-02-23 Soumendu Majee , Thilo Balke , Craig A. J. Kemp , Gregery T. Buzzard , Charles A. Bouman

Efficient and accurate multi-organ segmentation from abdominal CT volumes is a fundamental challenge in medical image analysis. Existing 3D segmentation approaches are computationally and memory intensive, often processing entire volumes…

Image and Video Processing · Electrical Eng. & Systems 2025-05-19 Hania Ghouse , Muzammil Behzad

3D Gaussian Splatting can exploit frustum culling and level-of-detail strategies to accelerate rendering of scenes containing a large number of primitives. However, the semi-transparent nature of Gaussians prevents the application of…

Computer Vision and Pattern Recognition · Computer Science 2026-04-21 Brent Zoomers , Florian Hahlbohm , Joni Vanherck , Lode Jorissen , Marcus Magnor , Nick Michiels

Volume electron microscopy (vEM) enables nanoscale 3D imaging of biological structures but remains constrained by acquisition trade-offs, leading to anisotropic volumes with limited axial resolution. Existing deep learning methods seek to…

Computer Vision and Pattern Recognition · Computer Science 2026-03-16 Yumeng He , Zanwei Zhou , Yekun Zheng , Chen Liang , Yunbo Wang , Xiaokang Yang

Accurate 3D instance segmentation is crucial for high-quality scene understanding in the 3D vision domain. However, 3D instance segmentation based on 2D-to-3D lifting approaches struggle to produce precise instance-level segmentation, due…

Computer Vision and Pattern Recognition · Computer Science 2025-12-22 Chaolei Wang , Yang Luo , Jing Du , Siyu Chen , Yiping Chen , Ting Han

Conventional geometry-based SLAM systems lack dense 3D reconstruction capabilities since their data association usually relies on feature correspondences. Additionally, learning-based SLAM systems often fall short in terms of real-time…

Computer Vision and Pattern Recognition · Computer Science 2024-08-22 Zhongche Qu , Zhi Zhang , Cong Liu , Jianhua Yin

Current popular backbones in computer vision, such as Vision Transformers (ViT) and ResNets are trained to perceive the world from 2D images. However, to more effectively understand 3D structural priors in 2D backbones, we propose Mask3D to…

Computer Vision and Pattern Recognition · Computer Science 2023-03-01 Ji Hou , Xiaoliang Dai , Zijian He , Angela Dai , Matthias Nießner

Single-view 3D hair reconstruction is challenging, due to the wide range of shape variations among diverse hairstyles. Current state-of-the-art methods are specialized in recovering un-braided 3D hairs and often take braided styles as their…

Computer Vision and Pattern Recognition · Computer Science 2024-09-26 Yujian Zheng , Yuda Qiu , Leyang Jin , Chongyang Ma , Haibin Huang , Di Zhang , Pengfei Wan , Xiaoguang Han

We present a new end-to-end learning framework to obtain detailed and spatially coherent reconstructions of multiple people from a single image. Existing multi-person methods suffer from two main drawbacks: they are often model-based and…

Computer Vision and Pattern Recognition · Computer Science 2021-04-20 Armin Mustafa , Akin Caliskan , Lourdes Agapito , Adrian Hilton

Single-view 3D object reconstruction is a fundamental and challenging computer vision task that aims at recovering 3D shapes from single-view RGB images. Most existing deep learning based reconstruction methods are trained and evaluated on…

Computer Vision and Pattern Recognition · Computer Science 2023-06-06 Xianghui Yang , Guosheng Lin , Luping Zhou

Inferring 3D locations and shapes of multiple objects from a single 2D image is a long-standing objective of computer vision. Most of the existing works either predict one of these 3D properties or focus on solving both for a single object.…

Computer Vision and Pattern Recognition · Computer Science 2021-11-08 Feng Liu , Xiaoming Liu

Advances in 3D reconstruction have enabled high-quality 3D capture, but require a user to collect hundreds to thousands of images to create a 3D scene. We present CAT3D, a method for creating anything in 3D by simulating this real-world…

Computer Vision and Pattern Recognition · Computer Science 2024-05-17 Ruiqi Gao , Aleksander Holynski , Philipp Henzler , Arthur Brussee , Ricardo Martin-Brualla , Pratul Srinivasan , Jonathan T. Barron , Ben Poole

3D Gaussian Splatting has emerged as an alternative 3D representation for novel view synthesis, benefiting from its high-quality rendering results and real-time rendering speed. However, the 3D Gaussians learned by 3D-GS have ambiguous…

Computer Vision and Pattern Recognition · Computer Science 2025-01-22 Xu Hu , Yuxi Wang , Lue Fan , Chuanchen Luo , Junsong Fan , Zhen Lei , Qing Li , Junran Peng , Zhaoxiang Zhang

Novel view synthesis (NVS) seeks to render photorealistic, 3D-consistent images of a scene from unseen camera poses given only a sparse set of posed views. Existing deterministic networks render observed regions quickly but blur unobserved…

Computer Vision and Pattern Recognition · Computer Science 2025-12-24 Thanh-Tung Le , Tuan Pham , Tung Nguyen , Deying Kong , Xiaohui Xie , Stephan Mandt
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