Teach CLIP to Develop a Number Sense for Ordinal Regression

Understand

Ordinal regression is a fundamental problem within the field of computer vision, with customised well-trained models on specific tasks.

• While pre-trained vision-language models (VLMs) have exhibited impressive performance on various vision tasks, their potential for ordinal regression has received less exploration.
• In this study, we first investigate CLIP's potential for ordinal regression, from which we expect the model could generalise to different ordinal regression tasks and scenarios.
• Unfortunately, vanilla CLIP fails on this task, since current VLMs have a well-documented limitation of encapsulating compositional concepts such as number sense.