54 Result(s)
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Article
Fixed-Lens camera setup and calibrated image registration for multifocus multiview 3D reconstruction
Image-based 3D reconstruction or 3D photogrammetry of small-scale objects including insects and biological specimens is challenging due to the use of a high magnification lens with inherently limited depth of ...
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Chapter and Conference Paper
Fast and Differentiable Message Passing on Pairwise Markov Random Fields
Despite the availability of many Markov Random Field (MRF) optimization algorithms, their widespread usage is currently limited due to imperfect MRF modelling arising from hand-crafted model parameters and the...
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Reference Work Entry In depth
Projective Reconstruction
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Article
Hallucinating Unaligned Face Images by Multiscale Transformative Discriminative Networks
Conventional face hallucination methods heavily rely on accurate alignment of low-resolution (LR) faces before upsampling them. Misalignment often leads to deficient results and unnatural artifacts for large u...
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Living Reference Work Entry In depth
Stereovision
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Article
Identity-Preserving Face Recovery from Stylized Portraits
Given an artistic portrait, recovering the latent photorealistic face that preserves the subject’s identity is challenging because the facial details are often distorted or fully lost in artistic portraits. We...
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Chapter and Conference Paper
Scalable Deep k-Subspace Clustering
Subspace clustering algorithms are notorious for their scalability issues because building and processing large affinity matrices are demanding. In this paper, we introduce a method that simultaneously learns ...
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Chapter and Conference Paper
Face Super-Resolution Guided by Facial Component Heatmaps
State-of-the-art face super-resolution methods leverage deep convolutional neural networks to learn a map** between low-resolution (LR) facial patterns and their corresponding high-resolution (HR) counterpar...
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Chapter and Conference Paper
Action Anticipation with RBF Kernelized Feature Map** RNN
We introduce a novel Recurrent Neural Network-based algorithm for future video feature generation and action anticipation called feature map** RNN. Our novel RNN architecture builds upon three effective prin...
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Chapter
Dictionary Learning on Grassmann Manifolds
Sparse representations have recently led to notable results in various visual recognition tasks. In a separate line of research, Riemannian manifolds have been shown useful for dealing with features and models...
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Article
A Generalized Projective Reconstruction Theorem and Depth Constraints for Projective Factorization
This paper presents a generalized version of the classic projective reconstruction theorem which helps to choose or assess depth constraints for projective depth estimation algorithms. The theorem shows that p...
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Article
Extrinsic Methods for Coding and Dictionary Learning on Grassmann Manifolds
Sparsity-based representations have recently led to notable results in various visual recognition tasks. In a separate line of research, Riemannian manifolds have been shown useful for dealing with features an...
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Article
\({L_q}\) -Closest-Point to Affine Subspaces Using the Generalized Weiszfeld Algorithm
This paper presents a method for finding an \(L_q\) ...
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Reference Work Entry In depth
Projective Reconstruction
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Chapter and Conference Paper
Globally Optimal Inlier Set Maximization with Unknown Rotation and Focal Length
Identifying inliers and outliers among data is a fundamental problem for model estimation. This paper considers models composed of rotation and focal length, which typically occurs in the context of panoramic ...
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Chapter and Conference Paper
Expanding the Family of Grassmannian Kernels: An Embedding Perspective
Modeling videos and image-sets as linear subspaces has proven beneficial for many visual recognition tasks. However, it also incurs challenges arising from the fact that linear subspaces do not obey Euclidean ...
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Chapter and Conference Paper
From Manifold to Manifold: Geometry-Aware Dimensionality Reduction for SPD Matrices
Representing images and videos with Symmetric Positive Definite (SPD) matrices and considering the Riemannian geometry of the resulting space has proven beneficial for many recognition tasks. Unfortunately, co...
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Article
Rotation Averaging
This paper is conceived as a tutorial on rotation averaging, summarizing the research that has been carried out in this area; it discusses methods for single-view and multiple-view rotation averaging, as well ...
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Chapter and Conference Paper
A Multiple Model Probability Hypothesis Density Tracker for Time-Lapse Cell Microscopy Sequences
Quantitative analysis of the dynamics of tiny cellular and subcellular structures in time-lapse cell microscopy sequences requires the development of a reliable multi-target tracking method capable of tracking...
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Article
Verifying Global Minima for L 2 Minimization Problems in Multiple View Geometry
We consider the least-squares (L2) minimization problems in multiple view geometry for triangulation, homography, camera resectioning and structure-and-motion with known rotation, or known plane. Although opti...
