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In the field of architecture, the conversion of single images into 2 and 1/2D and 3D meshes is a promising technology that enhances design visualization and efficiency. This paper evaluates four innovative methods: "One-2-3-45," "CRM:…

Graphics · Computer Science 2024-07-30 Jacob Sam , Karan Patel , Mike Saad

Acquiring 3D geometry of real world objects has various applications in 3D digitization, such as navigation and content generation in virtual environments. Image remains one of the most popular media for such visual tasks due to its…

Computer Vision and Pattern Recognition · Computer Science 2017-01-26 Shuai Du , Youyi Zheng

This paper presents a simple yet powerful method for 3D human mesh reconstruction from a single RGB image. Most recently, the non-local interactions of the whole mesh vertices have been effectively estimated in the transformer while the…

Computer Vision and Pattern Recognition · Computer Science 2023-04-20 Jeonghwan Kim , Mi-Gyeong Gwon , Hyunwoo Park , Hyukmin Kwon , Gi-Mun Um , Wonjun Kim

Finding localized correspondences across different images of the same object is crucial to understand its geometry. In recent years, this problem has seen remarkable progress with the advent of deep learning-based local image features and…

Computer Vision and Pattern Recognition · Computer Science 2024-01-31 Arjun Karpur , Guilherme Perrotta , Ricardo Martin-Brualla , Howard Zhou , André Araujo

Advancements in optical metrology has enabled documentation of dense 3D point clouds of cultural heritage sites. For large scale and continuous digital documentation, processing of dense 3D point clouds becomes computationally cumbersome,…

Computer Vision and Pattern Recognition · Computer Science 2022-04-07 Reza Maalek , Shahrokh Maalek

Mapping is an important part of many robotic applications. In order to measure the performance of the mapping process we have to measure the quality of its result: the map. The map is essential for robotic algorithms like localization and…

Robotics · Computer Science 2019-12-04 Sören Schwertfeger , Tianyan Yu

Understanding complex phenomena often requires analyzing high-dimensional data to uncover emergent properties that arise from multifactorial interactions. Here, we present EMUSES (Emerging-properties Mapping Using Spatial Embedding…

Emerging Technologies · Computer Science 2024-06-21 Chris Foulon , Marcela Ovando-Tellez , Lia Talozzi , Maurizio Corbetta , Anna Matsulevits , Michel Thiebaut de Schotten

Statistical shape analysis is a very useful tool in a wide range of medical and biological applications. However, it typically relies on the ability to produce a relatively small number of features that can capture the relevant variability…

Computer Vision and Pattern Recognition · Computer Science 2020-06-16 Riddhish Bhalodia , Ladislav Kavan , Ross Whitaker

Face recognition is a widely accepted biometric verification tool, as the face contains a lot of information about the identity of a person. In this study, a 2-step neural-based pipeline is presented for matching 3D facial shape to multiple…

Computer Vision and Pattern Recognition · Computer Science 2020-10-19 Soha Sadat Mahdi , Nele Nauwelaers , Philip Joris , Giorgos Bouritsas , Shunwang Gong , Sergiy Bokhnyak , Susan Walsh , Mark D. Shriver , Michael Bronstein , Peter Claes , .

Segmenting arbitrary 3D objects into constituent parts that are structurally meaningful is a fundamental problem encountered in a wide range of computer graphics applications. Existing methods for 3D shape segmentation suffer from complex…

Graphics · Computer Science 2020-10-23 Cheng Lin , Lingjie Liu , Changjian Li , Leif Kobbelt , Bin Wang , Shiqing Xin , Wenping Wang

Photometric Stereo methods seek to reconstruct the 3d shape of an object from motionless images obtained with varying illumination. Most existing methods solve a restricted problem where the physical reflectance model, such as Lambertian…

Computer Vision and Pattern Recognition · Computer Science 2021-10-06 Ofer Bartal , Nati Ofir , Yaron Lipman , Ronen Basri

We propose approaches based on deep learning to localize objects in images when only a small training dataset is available and the images have low quality. That applies to many problems in medical image processing, and in particular to the…

Computer Vision and Pattern Recognition · Computer Science 2018-11-20 Aaron Pries , Peter J. Schreier , Artur Lamm , Stefan Pede , Jürgen Schmidt

This paper presents a strategy to guide a mobile ground robot equipped with a camera or depth sensor, in order to autonomously map the visible part of a bounded three-dimensional structure. We describe motion planning algorithms that…

Robotics · Computer Science 2017-11-15 Manikandasriram Srinivasan Ramanagopal , André Phu-Van Nguyen , Jerome Le Ny

The paper presents a new model for single channel images low-level interpretation. The image is decomposed into a graph which captures a complete set of structural features. The description allows to accurately identify every edge location…

Computer Vision and Pattern Recognition · Computer Science 2019-04-23 Alessandro Dal Palu'

The Structure from Motion (SfM) challenge in computer vision is the process of recovering the 3D structure of a scene from a series of projective measurements that are calculated from a collection of 2D images, taken from different…

Computer Vision and Pattern Recognition · Computer Science 2023-04-06 Joseph Rowell

This position paper argues for the use of \emph{structured generative models} (SGMs) for the understanding of static scenes. This requires the reconstruction of a 3D scene from an input image (or a set of multi-view images), whereby the…

Computer Vision and Pattern Recognition · Computer Science 2024-12-16 Christopher K. I. Williams

Aerial image registration or matching is a geometric process of aligning two aerial images captured in different environments. Estimating the precise transformation parameters is hindered by various environments such as time, weather, and…

Computer Vision and Pattern Recognition · Computer Science 2021-07-20 Myeong-Seok Oh , Yong-Ju Lee , Seong-Whan Lee

We propose 3D Congealing, a novel problem of 3D-aware alignment for 2D images capturing semantically similar objects. Given a collection of unlabeled Internet images, our goal is to associate the shared semantic parts from the inputs and…

Computer Vision and Pattern Recognition · Computer Science 2024-04-03 Yunzhi Zhang , Zizhang Li , Amit Raj , Andreas Engelhardt , Yuanzhen Li , Tingbo Hou , Jiajun Wu , Varun Jampani

Modeling outdoor scenes for the synthetic 3D environment requires the recovery of reflectance/albedo information from raw images, which is an ill-posed problem due to the complicated unmodeled physics in this process (e.g., indirect…

Computer Vision and Pattern Recognition · Computer Science 2024-09-23 Shuang Song , Rongjun Qin

Modern scene reconstruction methods are able to accurately recover 3D surfaces that are visible in one or more images. However, this leads to incomplete reconstructions, missing all occluded surfaces. While much progress has been made on…

Computer Vision and Pattern Recognition · Computer Science 2025-11-07 Sam Bahrami , Dylan Campbell