VASR

Visual Analogies of Situation Recognition (VASR) is a dataset for visual analogical mapping, adapting the classical word-analogy task into the visual domain. It contains 196K object transitions and 385K activity transitions. Experiments demonstrate that state-of-the-art models do well when distractors are chosen randomly (~86%), but struggle with carefully chosen distractors (~53%, compared to 90% human accuracy)

Source: VASR: Visual Analogies of Situation Recognition

Image Source:https://arxiv.org/pdf/2212.04542v1.pdf

Project Website: https://vasr-dataset.github.io/