24 citations · 30 across the 5 of their papers we have counts for
6 papers
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…
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…
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…
Enhanced Performance of Pre-Trained Networks by Matched Augmentation Distributions
Touqeer Ahmad, Mohsen Jafarzadeh, Akshay Raj Dhamija +4
There exists a distribution discrepancy between training and testing, in the way images are fed to modern CNNs. Recent work tried to bridge this gap either by fine-tuning or re-tra…
A Unifying Framework for Formal Theories of Novelty:Framework, Examples and Discussion
T. E. Boult, P. A. Grabowicz, D. S. Prijatelj +11
Managing inputs that are novel, unknown, or out-of-distribution is critical as an agent moves from the lab to the open world. Novelty-related problems include being tolerant to nov…
A Review of Open-World Learning and Steps Toward Open-World Learning Without Labels
Mohsen Jafarzadeh, Akshay Raj Dhamija, Steve Cruz +3
In open-world learning, an agent starts with a set of known classes, detects, and manages things that it does not know, and learns them over time from a non-stationary stream of da…