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This work introduces an effective and practical solution to the dense two-view structure from motion (SfM) problem. One vital question addressed is how to mindfully use per-pixel optical flow correspondence between two frames for accurate…

Computer Vision and Pattern Recognition · Computer Science 2023-02-14 Weirong Chen , Suryansh Kumar , Fisher Yu

Given a set of observations, feature acquisition is about finding the subset of unobserved features which would enhance accuracy. Such problems have been explored in a sequential setting in prior work. Here, the model receives feedback from…

Machine Learning · Computer Science 2023-12-21 Vedang Asgaonkar , Aditya Jain , Abir De

Neural Radiance Fields (NeRF) has become a popular framework for learning implicit 3D representations and addressing different tasks such as novel-view synthesis or depth-map estimation. However, in downstream applications where decisions…

Computer Vision and Pattern Recognition · Computer Science 2021-09-29 Jianxiong Shen , Adria Ruiz , Antonio Agudo , Francesc Moreno-Noguer

Without manually annotated identities, unsupervised multi-object trackers are inferior to learning reliable feature embeddings. It causes the similarity-based inter-frame association stage also be error-prone, where an uncertainty problem…

Computer Vision and Pattern Recognition · Computer Science 2023-12-21 Kai Liu , Sheng Jin , Zhihang Fu , Ze Chen , Rongxin Jiang , Jieping Ye

Localisation with Frequency-Modulated Continuous-Wave (FMCW) radar has gained increasing interest due to its inherent resistance to challenging environments. However, complex artefacts of the radar measurement process require appropriate…

Robotics · Computer Science 2023-06-23 Jianhao Yuan , Paul Newman , Matthew Gadd

Advanced deepfake technologies are blurring the lines between real and fake, presenting both revolutionary opportunities and alarming threats. While it unlocks novel applications in fields like entertainment and education, its malicious use…

Computer Vision and Pattern Recognition · Computer Science 2026-04-21 Qihao Shen , Jiaxing Xuan , Zhenguang Liu , Sifan Wu , Yutong Xie , Zhaoyan Ming , Yingying Jiao , kui Ren

This paper studies the utility of techniques within uncertainty quantification, namely spectral projection and polynomial chaos expansion, in reducing sampling needs for characterizing acoustic metamaterial dispersion band responses given…

Uncertainty quantification for Particle Image Velocimetry (PIV) is critical for comparing flow fields with Computational Fluid Dynamics (CFD) results, and model design and validation. However, PIV features a complex measurement chain with…

Fluid Dynamics · Physics 2021-07-07 Lalit K. Rajendran , Sayantan Bhattacharya , Sally P. M. Bane , Pavlos P. Vlachos

We scale perceived distances of the core-set algorithm by a factor of uncertainty and search for low-confidence configurations, finding significant improvements in sample efficiency across CIFAR10/100 and SVHN image classification,…

Machine Learning · Computer Science 2022-02-10 Yuchen Li , Frank Rudzicz

Multi-frequency subspace migration imaging technique are usually adopted for the non-iterative imaging of unknown electromagnetic targets such as cracks in the concrete walls or bridges, anti-personnel mines in the ground, etc. in the…

Mathematical Physics · Physics 2014-12-23 Won-Kwang Park

Nuclear Magnetic Resonance (NMR) spectrometry uses electro-frequency pulses to probe the resonance of a compound's nucleus, which is then analyzed to determine its structure. The acquisition time of high-resolution NMR spectra remains a…

Background: Even though data visualizations (and underlying data) almost always contain uncertainty, it remains complex to communicate and interpret uncertainty representations. Consequently, uncertainty visualizations for non-expert…

An accurate treatment of electronic spectra in large systems with a technique such as time dependent density functional theory (TDDFT) is computationally challenging. Due to the Nyquist sampling theorem, direct real time simulations must be…

Materials Science · Physics 2024-01-17 Matthias Kick , Ezra Alexander , Anton Beiersdorfer , Troy Van Voorhis

Uncertainty quantification of the photogrammetry process is essential for providing per-point accuracy credentials of the point clouds. Unlike airborne LiDAR, whose accuracy generally remains consistent with objects with varying geometric…

Computer Vision and Pattern Recognition · Computer Science 2026-05-01 Debao Huang , Rongjun Qin

Visible-infrared object detection has gained sufficient attention due to its detection performance in low light, fog, and rain conditions. However, visible and infrared modalities captured by different sensors exist the information…

Computer Vision and Pattern Recognition · Computer Science 2025-11-17 Wencong Wu , Xiuwei Zhang , Hanlin Yin , Shun Dai , Hongxi Zhang , Yanning Zhang

Frequency estimation from measurements corrupted by noise is a fundamental challenge across numerous engineering and scientific fields. Among the pivotal factors shaping the resolution capacity of any frequency estimation technique are…

Signal Processing · Electrical Eng. & Systems 2024-09-23 Sampath Kumar Dondapati , Omkar Nitsure , Satish Mulleti

The process of 3D scene reconstruction can be affected by numerous uncertainty sources in real-world scenes. While Neural Radiance Fields (NeRFs) and 3D Gaussian Splatting (GS) achieve high-fidelity rendering, they lack built-in mechanisms…

Computer Vision and Pattern Recognition · Computer Science 2024-09-11 Marcus Klasson , Riccardo Mereu , Juho Kannala , Arno Solin

In this paper, we propose a method to solve the image restoration problem, which tries to restore the details of a corrupted image, especially due to the loss caused by JPEG compression. We have treated an image in the frequency domain to…

Computer Vision and Pattern Recognition · Computer Science 2018-05-24 Jaeyoung Yoo , Sang-ho Lee , Nojun Kwak

Despite advancements in electron backscatter diffraction (EBSD) detector speeds, the acquisition rates of 4-Dimensional (4D) EBSD data, i.e., a collection of 2-dimensional (2D) diffraction maps for every position of a convergent electron…

Signal Processing · Electrical Eng. & Systems 2023-08-02 Zoë Broad , Daniel Nicholls , Jack Wells , Alex W. Robinson , Amirafshar Moshtaghpour , Robert Masters , Louise Hughes , Nigel D. Browning

This paper draws a proposal of a set of parameters and methods for accuracy evaluation of visual inspection systems. The case of a monochrome board is treated, but practically all conclusions and methods may be extended for colour…

Computer Vision and Pattern Recognition · Computer Science 2008-03-04 Radu Arsinte , Costin Miron
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