2024 Learning to minify photometric stereo

Learning to minify photometric stereo

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August undefined, 2024

NettetWe present an automated machine learning approach for uncalibrated photometric stereo (PS). Our work aims at discovering lightweight and computationally efficient PS neural networks with excellent surface normal accuracy. Unlike previous uncalibrated deep PS networks, which are handcrafted and carefully tuned, we leverage differentiable … Nettet1. nov. 2024 · Existing learning-based photometric stereo methods and defect detection methods have achieved good performance in their respective fields. ... Y. Learning to …

NormAttention-PSN: A High-frequency Region Enhanced Photometric Stereo …

NettetThis is the code of paper "Learning to minify photometric stereo, CVPR2024". The code is based on python and keras. - Learning-to-Minify-Photometric-Stereo/README.md at master · junxuan-l... NettetLMPS (Learning to Minify Photometric Stereo[13] relax this constraint so that data with order-) ... photometric stereo methods to outdoor scenarios (i.e., a partly cloudy or … chasselay ehpad

Learning-to-Minify-Photometric-Stereo This is the code of …

Nettet4. des. 2024 · Photometric stereo recovers the surface normals of a 3D object from varying shading cues, prevailing in its capability for generating fine surface normal. In … Nettet17. mai 2024 · Photometric stereo is a technique for estimating normals of an object surface from its images taken under different light source directions. ... Li, J., Robles-Kelly, A., You, S., Matsushita, Y.: Learning to minify photometric stereo. In: Proceedings of the IEEE CVPR 2024, pp. 7568–7576 (2024) Google Scholar Nettet1. apr. 2024 · Photometric stereo is a technique for estimating the surface normal of an object by a set of images captured under different lighting conditions. Generally … custom builders in northern virginia

Minifying photometric stereo via knowledge distillation-based …

PS-Transformer: Learning Sparse Photometric Stereo Network …

Nettet1. apr. 2024 · Photometric stereo is a technique for estimating the surface normal of an object by a set of images captured under different lighting conditions. Generally speaking, the literature can be divided into four groups, i.e., example based methods, least-squares methods, robust methods and deep learning methods [1], [2], [3]. NettetAlthough much effort has been made to address this issue, existing photometric stereo methods based on deep learning did not fully consider the influence of global–local features and deep-shallow features on the training process. How to combine multi-feature into a framework effectively to overcome their drawbacks has not been explored. custom builders in richmond vaNettet11. nov. 2024 · Photometric Stereo (PS) aims to reconstruct the 3D shape of an object given a set of images taken under different lights. Calibrated photometric stereo methods assume the light directions are known in all images [7, 15, 17, 31, 36, 45,46,47].However, it is quite a tedious and laborious effort to calibrate the light sources in all input images … chasselay location

"Nettet1. mar. 2024 · In this paper, we present a complete photometric stereo data acquisition and processing framework, as shown in Fig. 1, constructing inter- and intraframe feature representations based on an arbitrary number of unordered images captured under different lighting configurations for high-quality surface normal estimation of non … " - Learning to minify photometric stereo

Learning to minify photometric stereo

A deep-shallow and global–local multi-feature fusion network for ...

Photometric stereo estimates the surface normal given a set of images acquired under different illumination conditions. To deal with diverse factors involved in the image formation process, recent photometric stereo methods demand a large number of images as input. We propose a method that can dramatically decrease the demands on the number of images by learning the most informative ones under ... Nettet1. jun. 2024 · Based on the PSBDDS, we introduce a photometric-stereo-based defect detection framework, which takes images captured in multiple directional lights as input …

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Nettet20. jun. 2024 · Learning to Minify Photometric Stereo Abstract: Photometric stereo estimates the surface normal given a set of images acquired under different illumination … NettetPhotometric stereo aims to recover the surface normals of a 3D object from various shading cues, establishing the relationship between two-dimensional images and the object geometry. Traditional methods usually adopt simplified reflectance models to approximate the non-Lambertian surface properties, while recently, photometric …

NettetImplement Learning-to-Minify-Photometric-Stereo with how-to, Q&A, fixes, code snippets. kandi ratings - Low support, No Bugs, No Vulnerabilities. No License, Build not available. Nettet27. okt. 2024 · Photometric stereo aims to reconstruct 3D geometry by recovering the dense surface orientation of a 3D object from multiple images under differing ... You, S. D.; Matsushita, Y. Learning to minify photometric stereo. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 7560–7568, 2024 ...

Nettet1. feb. 2024 · Recovering 3D surfaces based on the photometric stereo is a challenging task, due to the non-Lambertian surface of real-world objects. Although much effort has been made to address this issue, existing photometric stereo methods based on deep learning did not fully consider the influence of global–local features and deep-shallow … NettetHaofeng Hu. , Boxin Shi. Authors Info & Claims. NIPS'20: Proceedings of the 34th International Conference on Neural Information Processing SystemsDecember 2024 …

Nettet23. okt. 2024 · Single-View Photometric Stereo (PS). Traditional PS methods rely on outlier rejection [37, 58, 59], reflectance model fitting [10, 18, 51], or exemplars [15, 16] to deal with non-Lambertian surfaces.Deep learning based PS methods solve this problem by learning the surface reflectance prior from a dataset [7, 8, 17, 31, 44, 49].These …

NettetLearning to Minify Photometric Stereo Junxuan Li 1;2Antonio Robles-Kelly3 Shaodi You Yasuyuki Matsushita4 1Australian National University, College of Eng. and Comp. Sci., … custom builders in ocean shores waNettetPhotometric stereo estimates the surface normal given a set of images acquired under different illumination conditions. To deal with diverse factors involved in the image … chasselay mediathequeNettet26. jan. 2024 · PDF Industrial machine vision applications frequently employ Photometric Stereo (PS) ... Learning to Minify Photometric Stereo. Conference Paper. Jun 2024; Junxuan Li; Antonio Robles-Kelly; custom builders in springfieldNettet27. okt. 2024 · Photometric stereo aims to reconstruct 3D geometry by recovering the dense surface orientation of a 3D object from multiple images under differing … custom builders lancaster paNettet1. apr. 2024 · Photometric stereo is a technique for estimating the surface normal of an object by a set of images captured under different lighting conditions. Generally speaking, the literature can be divided into four groups, i.e., example based methods, least-squares methods, robust methods and deep learning methods [1], [2], [3]. chasselay menu cantineNettet1. nov. 2024 · Existing learning-based photometric stereo methods and defect detection methods have achieved good performance in their respective fields. However, ... custom builders jasper gaNettetand deep-learning based photometric stereo methods for non-Lambertian objects. For a detailed introduction of recent stud-ies of photometricstereo, readers can refer to [14]. … custom builders in venice fl