16 citations · 44 across the 13 of their papers we have counts for
13 papers
Improving the Robustness of 3D Human Pose Estimation: A Benchmark and Learning from Noisy Input
Trung-Hieu Hoang, Mona Zehni, Huy Phan +2
Despite the promising performance of current 3D human pose estimation techniques, understanding and enhancing their generalization on challenging in-the-wild videos remain an open…
Orthogonal Matrix Retrieval with Spatial Consensus for 3D Unknown-View Tomography
Shuai Huang, Mona Zehni, Ivan Dokmanić +1
Unknown-view tomography (UVT) reconstructs a 3D density map from its 2D projections at unknown, random orientations. A line of work starting with Kam (1980) employs the method of m…
Towards a Comprehensive Solution for a Vision-based Digitized Neurological Examination
Trung-Hieu Hoang, Mona Zehni, Huaijin Xu +3
The ability to use digitally recorded and quantified neurological exam information is important to help healthcare systems deliver better care, in-person and via telehealth, as the…
An Adversarial Learning Based Approach for Unknown View Tomographic Reconstruction
Mona Zehni, Zhizhen Zhao
The goal of 2D tomographic reconstruction is to recover an image given its projections from various views. It is often presumed that projection angles associated with the projectio…
Joint Learning of Portrait Intrinsic Decomposition and Relighting
Mona Zehni, Shaona Ghosh, Krishna Sridhar +1
Inverse rendering is the problem of decomposing an image into its intrinsic components, i.e. albedo, normal and lighting. To solve this ill-posed problem from single image, state-o…
DeepQAMVS: Query-Aware Hierarchical Pointer Networks for Multi-Video Summarization
Safa Messaoud, Ismini Lourentzou, Assma Boughoula +4
The recent growth of web video sharing platforms has increased the demand for systems that can efficiently browse, retrieve and summarize video content. Query-aware multi-video sum…
MSR-GAN: Multi-Segment Reconstruction via Adversarial Learning
Mona Zehni, Zhizhen Zhao
Multi-segment reconstruction (MSR) is the problem of estimating a signal given noisy partial observations. Here each observation corresponds to a randomly located segment of the si…
UVTomo-GAN: An adversarial learning based approach for unknown view X-ray tomographic reconstruction
Mona Zehni, Zhizhen Zhao
Tomographic reconstruction recovers an unknown image given its projections from different angles. State-of-the-art methods addressing this problem assume the angles associated with…
3D unknown view tomography via rotation invariants
Mona Zehni, Shuai Huang, Ivan Dokmanić +1
In this paper, we study the problem of reconstructing a 3D point source model from a set of 2D projections at unknown view angles. Our method obviates the need to recover the proje…
Joint Angular Refinement and Reconstruction for Single-Particle Cryo-EM
Mona Zehni, Laurène Donati, Emmanuel Soubies +2
Single-particle cryo-electron microscopy (cryo-EM) reconstructs the three-dimensional (3D) structure of bio-molecules from a large set of 2D projection images with random and unkno…
Geometric Invariants for Sparse Unknown View Tomography
Mona Zehni, Shuai Huang, Ivan Dokmanić +1
In this paper, we study a 2D tomography problem for point source models with random unknown view angles. Rather than recovering the projection angles, we reconstruct the model thro…
A Spectral Method for Stable Bispectrum Inversion with Application to Multireference Alignment
Hua Chen, Mona Zehni, Zhizhen Zhao
We focus on an alignment-free method to estimate the underlying signal from a large number of noisy randomly shifted observations. Specifically, we estimate the mean, power spectru…
Multi-Segment Reconstruction Using Invariant Features
Mona Zehni, Minh N. Do, Zhizhen Zhao
Multi-segment reconstruction (MSR) problem consists of recovering a signal from noisy segments with unknown positions of the observation windows. One example arises in DNA sequence…