4 papers
Allowing humans to interactively guide machines where to look does not always improve human-AI team's classification accuracy
Giang Nguyen, Mohammad Reza Taesiri, Sunnie S. Y. Kim +1
Via thousands of papers in Explainable AI (XAI), attention maps \cite{vaswani2017attention} and feature importance maps \cite{bansal2020sam} have been established as a common means…
WiCV@CVPR2023: The Eleventh Women In Computer Vision Workshop at the Annual CVPR Conference
Doris Antensteiner, Marah Halawa, Asra Aslam +6
In this paper, we present the details of Women in Computer Vision Workshop - WiCV 2023, organized alongside the hybrid CVPR 2023 in Vancouver, Canada. WiCV aims to amplify the voic…
Humans, AI, and Context: Understanding End-Users' Trust in a Real-World Computer Vision Application
Sunnie S. Y. Kim, Elizabeth Anne Watkins, Olga Russakovsky +2
Trust is an important factor in people's interactions with AI systems. However, there is a lack of empirical studies examining how real end-users trust or distrust the AI system th…
UFO: A unified method for controlling Understandability and Faithfulness Objectives in concept-based explanations for CNNs
Vikram V. Ramaswamy, Sunnie S. Y. Kim, Ruth Fong +1
Concept-based explanations for convolutional neural networks (CNNs) aim to explain model behavior and outputs using a pre-defined set of semantic concepts (e.g., the model recogniz…