1 code implementation • 20 Jul 2022 • Xingjian Zhen, Zihang Meng, Rudrasis Chakraborty, Vikas Singh
Comparing the functional behavior of neural network models, whether it is a single network over time or two (or more networks) during or post-training, is an essential step in understanding what they are learning (and what they are not), and for identifying strategies for regularization or efficiency improvements.
1 code implementation • 2 Dec 2021 • Zihang Meng, David Yang, Xuefei Cao, Ashish Shah, Ser-Nam Lim
Our work in this paper overcomes this by harvesting objects corresponding to a given sentence from the training set, even if they don't belong to the same image.
1 code implementation • ICCV 2021 • 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.
1 code implementation • NeurIPS 2021 • 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.
1 code implementation • CVPR 2021 • Zihang Meng, Licheng Yu, Ning Zhang, Tamara Berg, Babak Damavandi, Vikas Singh, Amy Bearman
Learning the grounding of each word is challenging, due to noise in the human-provided traces and the presence of words that cannot be meaningfully visually grounded.
no code implementations • 31 Jan 2021 • Teja Kanchinadam, Zihang Meng, Joseph Bockhorst, Vikas Singh Kim, Glenn Fung
Customer satisfaction is an important factor in creating and maintaining long-term relationships with customers.
no code implementations • NeurIPS 2021 • Zihang Meng, Lopamudra Mukherjee, Vikas Singh, Sathya N. Ravi
We propose a framework which makes it feasible to directly train deep neural networks with respect to popular families of task-specific non-decomposable per- formance measures such as AUC, multi-class AUC, F -measure and others, as well as models such as non-negative matrix factorization.
no code implementations • 1 Jan 2021 • Zihang Meng, Rudrasis Chakraborty, Vikas Singh
We present an efficient stochastic algorithm (RSG+) for canonical correlation analysis (CCA) derived via a differential geometric perspective of the underlying optimization task.
3 code implementations • 30 Apr 2020 • Zihang Meng, Sathya N. Ravi, Vikas Singh
We describe our development and show the use of our solver in a video segmentation task and meta-learning for few-shot learning.
no code implementations • 16 May 2019 • Owen Levin, Zihang Meng, Vikas Singh, Xiaojin Zhu
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.
1 code implementation • ECCV 2018 • Zihang Meng, Nagesh Adluru, Hyunwoo J. Kim, Glenn Fung, Vikas Singh
A sizable body of work on relative attributes provides compelling evidence that relating pairs of images along a continuum of strength pertaining to a visual attribute yields significant improvements in a wide variety of tasks in vision.
no code implementations • 21 Dec 2017 • Jiefeng Chen, Zihang Meng, Changtian Sun, Wei Tang, Yinglun Zhu
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.