Bayesian Exploration of Pre-trained Models for Low-shot Image Classification

arXiv:2404.00312v1 Announce Type: new
Abstract: Low-shot image classification is a fundamental task in computer vision, and the emergence of large-scale vision-language models such as CLIP has greatly advanced the forefront of research in this field. However, most existing CLIP-based methods lack the flexibility to effectively incorporate other pre-trained models that encompass knowledge distinct from CLIP. To bridge the gap, this work proposes a simple and effective probabilistic model ensemble framework based on Gaussian processes, which have previously demonstrated remarkable efficacy …

abstract advanced arxiv bayesian classification clip computer computer vision cs.ai cs.cv emergence exploration flexibility however image language language models low pre-trained models research scale type vision vision-language models