activity
20192025
most citedAnalyzing Worldwide Social Distancing through Large-Scale Computer Vision

15 citations · 40 across the 10 of their papers we have counts for

collaborators
Showing cs.CVShow all

8 papers · 1 filter

cs.CV2022★ 3 cited

Why Accuracy Is Not Enough: The Need for Consistency in Object Detection

Caleb Tung, Abhinav Goel, Fischer Bordwell +4

Object detectors are vital to many modern computer vision applications. However, even state-of-the-art object detectors are not perfect. On two images that look similar to human ey…

cs.CV2022

Irrelevant Pixels are Everywhere: Find and Exclude Them for More Efficient Computer Vision

Caleb Tung, Abhinav Goel, Xiao Hu +5

Computer vision is often performed using Convolutional Neural Networks (CNNs). CNNs are compute-intensive and challenging to deploy on power-contrained systems such as mobile and I…

cs.CV2021

Efficient Computer Vision on Edge Devices with Pipeline-Parallel Hierarchical Neural Networks

Abhinav Goel, Caleb Tung, Xiao Hu +3

Computer vision on low-power edge devices enables applications including search-and-rescue and security. State-of-the-art computer vision algorithms, such as Deep Neural Networks (…

cs.CV2021★ 1 cited

Low-Power Multi-Camera Object Re-Identification using Hierarchical Neural Networks

Abhinav Goel, Caleb Tung, Xiao Hu +4

Low-power computer vision on embedded devices has many applications. This paper describes a low-power technique for the object re-identification (reID) problem: matching a query im…

cs.CV2020★ 15 cited

Analyzing Worldwide Social Distancing through Large-Scale Computer Vision

Isha Ghodgaonkar, Subhankar Chakraborty, Vishnu Banna +15

In order to contain the COVID-19 pandemic, countries around the world have introduced social distancing guidelines as public health interventions to reduce the spread of the diseas…

cs.CV2020★ 8 cited

Low-Power Object Counting with Hierarchical Neural Networks

Abhinav Goel, Caleb Tung, Sara Aghajanzadeh +4

Deep Neural Networks (DNNs) can achieve state-of-the-art accuracy in many computer vision tasks, such as object counting. Object counting takes two inputs: an image and an object q…

cs.CV2020

A Survey of Methods for Low-Power Deep Learning and Computer Vision

Abhinav Goel, Caleb Tung, Yung-Hsiang Lu +1

Deep neural networks (DNNs) are successful in many computer vision tasks. However, the most accurate DNNs require millions of parameters and operations, making them energy, computa…

cs.CV2019★ 5 cited

Low-Power Computer Vision: Status, Challenges, Opportunities

Sergei Alyamkin, Matthew Ardi, Alexander C. Berg +41

Computer vision has achieved impressive progress in recent years. Meanwhile, mobile phones have become the primary computing platforms for millions of people. In addition to mobile…