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20162022
most citedUPSET and ANGRI : Breaking High Performance Image Classifiers

91 citations · 296 across the 23 of their papers we have counts for

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54 papers · 1 filter

cs.CV20221 cited

Scalable Vehicle Re-Identification via Self-Supervision

Pirazh Khorramshahi, Vineet Shenoy, Rama Chellappa

As Computer Vision technologies become more mature for intelligent transportation applications, it is time to ask how efficient and scalable they are for large-scale and real-time…

cs.CV20221 cited

Scalable and Real-time Multi-Camera Vehicle Detection, Re-Identification, and Tracking

Pirazh Khorramshahi, Vineet Shenoy, Michael Pack +1

Multi-camera vehicle tracking is one of the most complicated tasks in Computer Vision as it involves distinct tasks including Vehicle Detection, Tracking, and Re-identification. De…

cs.CV2021

LR-to-HR Face Hallucination with an Adversarial Progressive Attribute-Induced Network

Nitin Balachandran, Jun-Cheng Chen, Rama Chellappa

Face super-resolution is a challenging and highly ill-posed problem since a low-resolution (LR) face image may correspond to multiple high-resolution (HR) ones during the hallucina…

cs.CV2021

Finding Facial Forgery Artifacts with Parts-Based Detectors

Steven Schwarcz, Rama Chellappa

Manipulated videos, especially those where the identity of an individual has been modified using deep neural networks, are becoming an increasingly relevant threat in the modern da…

cs.CV2021

PASS: Protected Attribute Suppression System for Mitigating Bias in Face Recognition

Prithviraj Dhar, Joshua Gleason, Aniket Roy +2

Face recognition networks encode information about sensitive attributes while being trained for identity classification. Such encoding has two major issues: (a) it makes the face r…

cs.CV20215 cited

Unsupervised Super-Resolution of Satellite Imagery for High Fidelity Material Label Transfer

Arthita Ghosh, Max Ehrlich, Larry Davis +1

Urban material recognition in remote sensing imagery is a highly relevant, yet extremely challenging problem due to the difficulty of obtaining human annotations, especially on low…