Modern vision-language models have closed the gap with humans on complex scene understanding, but they still make different spatial reasoning choices than humans do—suggesting they process images differently even when achieving similar accuracy.
This paper tracks how vision-language models have improved at describing complex images over the past decade. The authors created a dataset of 100 images showing complex social interactions and compared how well different models describe them compared to humans.