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We study end-to-end learning strategies for 3D shape inference from images, in particular from a single image. Several approaches in this direction have been investigated that explore different shape representations and suitable learning…

Computer Vision and Pattern Recognition · Computer Science 2019-08-21 Roman Klokov , Jakob Verbeek , Edmond Boyer

Implicit curve and surface reconstruction attracts the attention of many researchers and gains a wide range of applications, due to its ability to describe objects with complicated geometry and topology. However, extra zero-level sets or…

Numerical Analysis · Mathematics 2019-09-04 Yusuf Fatihu Hamza , Hongwei Lin , Zihao Li

In this article we present a review of the Radon transform and the instability of the tomographic reconstruction process. We show some new mathematical results in tomography obtained by a variational formulation of the reconstruction…

Mathematical Physics · Physics 2015-06-17 Paolo Facchi , Marilena Ligabò , Sergio Solimini

Shapes do not define a linear space. This paper explores the linear structure of deformations as a representation of shapes. This transforms shape optimization to a variant of optimal control. The numerical challenges of this point of view…

Optimization and Control · Mathematics 2022-03-15 Stephan Schmidt , Volker H. Schulz

In this paper we study partial differential equations (PDEs) that can be used to model value adjustments. Different value adjustments denoted generally as xVA are nowadays added to the risk-free financial derivative values and the PDE…

Risk Management · Quantitative Finance 2021-07-21 Falko Baustian , Martin Fencl , Jan Pospíšil , Vladimír Švígler

When images are statistically described by a generative model we can use this information to develop optimum techniques for various image restoration problems as inpainting, super-resolution, image coloring, generative model inversion, etc.…

Image and Video Processing · Electrical Eng. & Systems 2020-06-17 Kalliopi Basioti , George V. Moustakides

Because of their strong theoretical properties, Shapley values have become very popular as a way to explain predictions made by black box models. Unfortuately, most existing techniques to compute Shapley values are computationally very…

Machine Learning · Computer Science 2022-08-29 Arne Gevaert , Yvan Saeys

The mathematics of K-conserving functional differentiation, with K being the integral of some invertible function of the functional variable, is clarified. The most general form for constrained functional derivatives is derived from the…

Mathematical Physics · Physics 2007-09-13 Tamas Gal

In this paper, we study the problem of image recovery from given partial (corrupted) observations. Recovering an image using a low-rank model has been an active research area in data analysis and machine learning. But often, images are not…

Computer Vision and Pattern Recognition · Computer Science 2020-03-13 Pawan Goyal , Hussam Al Daas , Peter Benner

In this report, we present and compare the results of an improved fractional and integer order partial differential equation (PDE)-based binarization scheme. The improved model incorporates a diffusion term in addition to the edge and…

Computer Vision and Pattern Recognition · Computer Science 2021-11-24 Uche A. Nnolim

Current state-of-the-art motion-based dynamic computed tomography reconstruction techniques estimate the deformation by considering motion models in the entire object volume although occasionally the proper change is local. In this article,…

Optimization and Control · Mathematics 2023-09-06 Anh-Tuan Nguyen , Jens Renders , Jan Sijbers , Jan De Beenhouwer

We investigate diagonal forms of degree $d$ over the function field $F$ of a smooth projective $p$-adic curve: if a form is isotropic over the completion of $F$ with respect to each discrete valuation of $F$, then it is isotropic over…

Number Theory · Mathematics 2021-04-13 Susanne Pumpluen

We present a novel approach to image restoration that leverages ideas from localized structured prediction and non-linear multi-task learning. We optimize a penalized energy function regularized by a sum of terms measuring the distance…

Machine Learning · Computer Science 2020-06-17 Thomas Eboli , Alex Nowak-Vila , Jian Sun , Francis Bach , Jean Ponce , Alessandro Rudi

The present paper deals with the interior solid-fluid interaction problem in harmonic regime with randomly perturbed boundaries. Analysis of the shape derivative and shape Hessian of vector- and tensor-valued functions is provided. Moments…

Numerical Analysis · Mathematics 2020-09-30 Debopriya Mukherjee , Thanh Tran

We introduce a new model of linear regression for random functional inputs taking into account the first order derivative of the data. We propose an estimation method which comes down to solving a special linear inverse problem. Our…

Statistics Theory · Mathematics 2016-08-16 André Mas , Besnik Pumo

Object recognition is still an impediment in the field of computer vision and multimedia retrieval.Defining an object model is a critical task. Shape information of an object play a critical role in the process of object recognition.…

Computer Vision and Pattern Recognition · Computer Science 2014-03-31 Akbar Khan , Pratap Reddy L

Learning a dense 3D model with fine-scale details from a single facial image is highly challenging and ill-posed. To address this problem, many approaches fit smooth geometries through facial prior while learning details as additional…

Computer Vision and Pattern Recognition · Computer Science 2022-03-21 Xingyu Ren , Alexandros Lattas , Baris Gecer , Jiankang Deng , Chao Ma , Xiaokang Yang , Stefanos Zafeiriou

There are many studies on development of models for analyzing some derivatives such as credit default swaps .

Pricing of Securities · Quantitative Finance 2017-06-20 Zahra Sokoot , Navideh Modarresi , Farzaneh Niknejad

In this paper, we discuss some problems of elementary plane differential geometry and kinematics. Although the results are not new, the consistent use of complex-valued functions (plane curves) of a real variable (parameter) allows to…

Differential Geometry · Mathematics 2024-07-08 Uwe Bäsel

In this paper, we analyze the error estimate of a wavelet frame based image restoration method from degraded and incomplete measurements. We present the error between the underlying original discrete image and the approximate solution which…

Analysis of PDEs · Mathematics 2022-08-23 Jian-Feng Cai , Jae Kyu Choi , Jianbin Yang
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