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Surface reconstruction from multiple, calibrated images is a challenging task - often requiring a large number of collected images with significant overlap. We look at the specific case of human foot reconstruction. As with previous…

Computer Vision and Pattern Recognition · Computer Science 2025-02-19 Oliver Boyne , Roberto Cipolla

Accurate 3D foot reconstruction is crucial for personalized orthotics, digital healthcare, and virtual fittings. However, existing methods struggle with incomplete scans and anatomical variations, particularly in self-scanning scenarios…

Computer Vision and Pattern Recognition · Computer Science 2025-08-19 Kyle Fogarty , Jing Yang , Chayan Kumar Patodi , Jack Foster , Aadi Bhanti , Steven Chacko , Cengiz Oztireli , Ujwal Bonde

In this paper we present a high fidelity and articulated 3D human foot model. The model is parameterised by a disentangled latent code in terms of shape, texture and articulated pose. While high fidelity models are typically created with…

Computer Vision and Pattern Recognition · Computer Science 2025-03-26 Oliver Boyne , James Charles , Roberto Cipolla

The development of large-scale 3D scene reconstruction and novel view synthesis methods mostly rely on datasets comprising perspective images with narrow fields of view (FoV). While effective for small-scale scenes, these datasets require…

Computer Vision and Pattern Recognition · Computer Science 2025-04-10 Ulas Gunes , Matias Turkulainen , Xuqian Ren , Arno Solin , Juho Kannala , Esa Rahtu

Reconstructing the underlying 3D surface of an object from a single image is a challenging problem that has received extensive attention from the computer vision community. Many learning-based approaches tackle this problem by learning a 3D…

Computer Vision and Pattern Recognition · Computer Science 2023-02-28 Nicolai Häni , Jun-Jee Chao , Volkan Isler

We introduce Intrinsic Image Fusion, a method that reconstructs high-quality physically based materials from multi-view images. Material reconstruction is highly underconstrained and typically relies on analysis-by-synthesis, which requires…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Peter Kocsis , Lukas Höllein , Matthias Nießner

4D scans of dynamic deformable human body parts help researchers have a better understanding of spatiotemporal features. However, reconstructing 4D scans based on multiple asynchronous cameras encounters two main challenges: 1) finding the…

Image and Video Processing · Electrical Eng. & Systems 2023-07-25 Farzam Tajdari , Toon Huysmans , Xinhe Yao , Jun Xu , Yu Song

Detecting anomalies in fundus images through unsupervised methods is a challenging task due to the similarity between normal and abnormal tissues, as well as their indistinct boundaries. The current methods have limitations in accurately…

Computer Vision and Pattern Recognition · Computer Science 2023-12-29 Jingqi Niu , Qinji Yu , Shiwen Dong , Zilong Wang , Kang Dang , Xiaowei Ding

Reconstructing high-fidelity 3D head geometry from images is critical for a wide range of applications, yet existing methods face fundamental limitations. Traditional photogrammetry achieves exceptional detail but requires extensive camera…

Computer Vision and Pattern Recognition · Computer Science 2026-03-30 Noé Artru , Rukhshanda Hussain , Emeline Got , Alexandre Messier , David B. Lindell , Abdallah Dib

We propose a novel method to accurately reconstruct a set of images representing a single scene from few linear multi-view measurements. Each observed image is modeled as the sum of a background image and a foreground one. The background…

Computer Vision and Pattern Recognition · Computer Science 2013-09-19 Gilles Puy , Pierre Vandergheynst

Fine-detailed reconstructions are in high demand in many applications. However, most of the existing RGB-D reconstruction methods rely on pre-calculated accurate camera poses to recover the detailed surface geometry, where the…

Computer Vision and Pattern Recognition · Computer Science 2022-10-25 Lu Sang , Bjoern Haefner , Xingxing Zuo , Daniel Cremers

Dense 3D reconstruction and tracking of dynamic scenes from monocular video remains an important open challenge in computer vision. Progress in this area has been constrained by the scarcity of high-quality datasets with dense, complete,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-07 Zeren Jiang , Yushi Lan , Yihang Luo , Yufan Deng , Zihang Lai , Edgar Sucar , Christian Rupprecht , Iro Laina , Diane Larlus , Chuanxia Zheng , Andrea Vedaldi

Real-world images used for training machine learning algorithms are often unstructured and inconsistent. The process of analysing and tagging these images can be costly and error prone (also availability, gaps and legal conundrums).…

Artificial Intelligence · Computer Science 2022-09-28 Jose Cerqueira Fernandes , Benjamin Kenwright

This paper introduces a device, algorithm and graphical user interface to obtain anthropometric measurements of foot. Presented device facilitates obtaining scale of image and image processing by taking one image from side foot and…

Computer Vision and Pattern Recognition · Computer Science 2017-07-12 Amir Mohammad Esmaieeli Sikaroudi , Sasan Ghaffari , Ali Yousefi , Hassan Sadeghi Naeini

State-of-the-art methods can recover accurate overall 3D human body motion from in-the-wild videos. However, they often fail to capture fine-grained articulations, especially in the feet, which are critical for applications such as gait…

Computer Vision and Pattern Recognition · Computer Science 2026-03-11 Tom Wehrbein , Bodo Rosenhahn

Due to their highly structured characteristics, faces are easier to recover than natural scenes for blind image super-resolution. Therefore, we can extract the degradation representation of an image from the low-quality and recovered face…

Computer Vision and Pattern Recognition · Computer Science 2023-09-18 Zhicun Yin , Ming Liu , Xiaoming Li , Hui Yang , Longan Xiao , Wangmeng Zuo

Recent years have seen the development of mature solutions for reconstructing deformable surfaces from a single image, provided that they are relatively well-textured. By contrast, recovering the 3D shape of texture-less surfaces remains an…

Computer Vision and Pattern Recognition · Computer Science 2018-07-30 Jan Bednařík , Pascal Fua , Mathieu Salzmann

Advances in computer vision, particularly in optical image-based 3D reconstruction and feature matching, enable applications like marker-less surgical navigation and digitization of surgery. However, their development is hindered by a lack…

Computer Vision and Pattern Recognition · Computer Science 2025-01-29 Emma Most , Jonas Hein , Frédéric Giraud , Nicola A. Cavalcanti , Lukas Zingg , Baptiste Brument , Nino Louman , Fabio Carrillo , Philipp Fürnstahl , Lilian Calvet

Robot footstep planning strategies can be divided in two main approaches: discrete searches and continuous optimizations. While discrete searches have been broadly applied, continuous optimizations approaches have been restricted for…

In this paper, we propose a novel method for joint recovery of camera pose, object geometry and spatially-varying Bidirectional Reflectance Distribution Function (svBRDF) of 3D scenes that exceed object-scale and hence cannot be captured…

Computer Vision and Pattern Recognition · Computer Science 2023-06-07 Carolin Schmitt , Božidar Antić , Andrei Neculai , Joo Ho Lee , Andreas Geiger
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