AI RESEARCH
ToolFG: Towards Well-Grounded Fine-Grained Image Classification
arXiv CS.CV
•
ArXi:2606.02518v1 Announce Type: new Fine-grained image classification (FGIC) has broad applications and has attracted significant research attention. In this paper, we explore a novel paradigm for solving FGIC by proposing \textbf{ToolFG}, the first tool-integrated MLLM-based framework tailored to FGIC. ToolFG enables MLLMs to autonomously and flexibly use external tools during the reasoning process, actively interact with images, and collect verifiable visual cues for distinguishing highly similar categories in a \textit{reliable} and \textit{well-grounded} manner.