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most citedSMART-Vision: Survey of Modern Action Recognition Techniques in Vision

17 citations · 19 across the 9 of their papers we have counts for

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cs.CV2025

2COOOL: 2nd Workshop on the Challenge Of Out-Of-Label Hazards in Autonomous Driving

Ali K. AlShami, Ryan Rabinowitz, Maged Shoman +9

As the computer vision community advances autonomous driving algorithms, integrating vision-based insights with sensor data remains essential for improving perception, decision mak…

cs.CV2025

COSTARR: Consolidated Open Set Technique with Attenuation for Robust Recognition

Ryan Rabinowitz, Steve Cruz, Walter Scheirer +1

Handling novelty remains a key challenge in visual recognition systems. Existing open-set recognition (OSR) methods rely on the familiarity hypothesis, detecting novelty by the abs…

cs.CV2025

GHOST: Gaussian Hypothesis Open-Set Technique

Ryan Rabinowitz, Steve Cruz, Manuel Günther +1

Evaluations of large-scale recognition methods typically focus on overall performance. While this approach is common, it often fails to provide insights into performance across ind…

cs.CV202517 cited

SMART-Vision: Survey of Modern Action Recognition Techniques in Vision

Ali K. AlShami, Ryan Rabinowitz, Khang Lam +4

Human Action Recognition (HAR) is a challenging domain in computer vision, involving recognizing complex patterns by analyzing the spatiotemporal dynamics of individuals' movements…

cs.CV20242 cited

COOOL: Challenge Of Out-Of-Label A Novel Benchmark for Autonomous Driving

Ali K. AlShami, Ananya Kalita, Ryan Rabinowitz +4

As the Computer Vision community rapidly develops and advances algorithms for autonomous driving systems, the goal of safer and more efficient autonomous transportation is becoming…

cs.CV2024

Watchlist Challenge: 3rd Open-set Face Detection and Identification

Furkan Kasım, Terrance E. Boult, Rensso Mora +8

In the current landscape of biometrics and surveillance, the ability to accurately recognize faces in uncontrolled settings is paramount. The Watchlist Challenge addresses this cri…