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20182022
most citedLooking GLAMORous: Vehicle Re-Id in Heterogeneous Cameras Networks with Global and Local Attention

24 citations · 48 across the 16 of their papers we have counts for

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8 papers · 1 filter

cs.CV2022

Targeted Attention for Generalized- and Zero-Shot Learning

Abhijit Suprem

The Zero-Shot Learning (ZSL) task attempts to learn concepts without any labeled data. Unlike traditional classification/detection tasks, the evaluation environment is provided uns…

cs.CV2022

ATEAM: Knowledge Integration from Federated Datasets for Vehicle Feature Extraction using Annotation Team of Experts

Abhijit Suprem, Purva Singh, Suma Cherkadi +3

The vehicle recognition area, including vehicle make-model recognition (VMMR), re-id, tracking, and parts-detection, has made significant progress in recent years, driven by severa…

cs.CV20221 cited

Constructive Interpretability with CoLabel: Corroborative Integration, Complementary Features, and Collaborative Learning

Abhijit Suprem, Sanjyot Vaidya, Suma Cherkadi +3

Machine learning models with explainable predictions are increasingly sought after, especially for real-world, mission-critical applications that require bias detection and risk mi…

cs.CV202011 cited

ODIN: Automated Drift Detection and Recovery in Video Analytics

Abhijit Suprem, Joy Arulraj, Calton Pu +1

Recent advances in computer vision have led to a resurgence of interest in visual data analytics. Researchers are developing systems for effectively and efficiently analyzing visua…

cs.CV202024 cited

Looking GLAMORous: Vehicle Re-Id in Heterogeneous Cameras Networks with Global and Local Attention

Abhijit Suprem, Calton Pu

Vehicle re-identification (re-id) is a fundamental problem for modern surveillance camera networks. Existing approaches for vehicle re-id utilize global features and local features…

cs.CV20202 cited

Small, Accurate, and Fast Vehicle Re-ID on the Edge: the SAFR Approach

Abhijit Suprem, Calton Pu, Joao Eduardo Ferreira

We propose a Small, Accurate, and Fast Re-ID (SAFR) design for flexible vehicle re-id under a variety of compute environments such as cloud, mobile, edge, or embedded devices by on…