6 citations · 11 across the 5 of their papers we have counts for
6 papers
Neural TMDlayer: Modeling Instantaneous flow of features via SDE Generators
Zihang Meng, Vikas Singh, Sathya N. Ravi
We study how stochastic differential equation (SDE) based ideas can inspire new modifications to existing algorithms for a set of problems in computer vision. Loosely speaking, our…
An Online Riemannian PCA for Stochastic Canonical Correlation Analysis
Zihang Meng, Rudrasis Chakraborty, Vikas Singh
We present an efficient stochastic algorithm (RSG+) for canonical correlation analysis (CCA) using a reparametrization of the projection matrices. We show how this reparametrizatio…
Connecting What to Say With Where to Look by Modeling Human Attention Traces
Zihang Meng, Licheng Yu, Ning Zhang +4
We introduce a unified framework to jointly model images, text, and human attention traces. Our work is built on top of the recent Localized Narratives annotation framework [30], w…
Graph Neural Networks to Predict Customer Satisfaction Following Interactions with a Corporate Call Center
Teja Kanchinadam, Zihang Meng, Joseph Bockhorst +2
Customer satisfaction is an important factor in creating and maintaining long-term relationships with customers. Near real-time identification of potentially dissatisfied customers…
Fooling Computer Vision into Inferring the Wrong Body Mass Index
Owen Levin, Zihang Meng, Vikas Singh +1
Recently it's been shown that neural networks can use images of human faces to accurately predict Body Mass Index (BMI), a widely used health indicator. In this paper we demonstrat…
ReabsNet: Detecting and Revising Adversarial Examples
Jiefeng Chen, Zihang Meng, Changtian Sun +2
Though deep neural network has hit a huge success in recent studies and applica- tions, it still remains vulnerable to adversarial perturbations which are imperceptible to humans.…