Omkar2118/datasets huggingface dataset:
VisAlign

**VisAlign** is a dataset for measuring AI-human visual alignment in terms of image classification, a fundamental task in machine perception. In order to evaluate AI-Human visual alignment, a dataset should encompass samples with various scenarios that may arise in the real world and have gold human perception labels. The dataset consists of three groups of samples, namely Must-Act (i.e., Must-Classify), Must-Abstain, and Uncertain, based on the quantity and clarity of visual information in an image and further divided into eight categories.

Introducing paper: VisAlign: Dataset for Measuring the Degree of Alignment between AI and Humans in Visual Perception
CAER

Jiyoung Lee, Seungryong Kim, Sunok Kim, Jungin Park, Kwanghoon Sohn; Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2019, pp. 10143-10152