11 papers
Learning from Medical Entity Trees: An Entity-Centric Medical Data Engineering Framework for MLLMs
Jianghang Lin, Haihua Yang, Deli Yu +6
Multimodal Large Language Models (MLLMs) have shown transformative potential in medical applications, yet their performance is hindered by conventional data curation strategies tha…
Referring Industrial Anomaly Segmentation
Pengfei Yue, Xiaokang Jiang, Yilin Lu +3
Industrial Anomaly Detection (IAD) is vital for manufacturing, yet traditional methods face significant challenges: unsupervised approaches yield rough localizations requiring manu…
Evolving, Not Training: Zero-Shot Reasoning Segmentation via Evolutionary Prompting
Kai Ye, Xiaotong You, Jianghang Lin +3
Reasoning Segmentation requires models to interpret complex, context-dependent linguistic queries to achieve pixel-level localization. Current dominant approaches rely heavily on S…
Understanding What Is Not Said:Referring Remote Sensing Image Segmentation with Scarce Expressions
Kai Ye, Bowen Liu, Jianghang Lin +3
Referring Remote Sensing Image Segmentation (RRSIS) aims to segment instances in remote sensing images according to referring expressions. Unlike Referring Image Segmentation on ge…
Generate Aligned Anomaly: Region-Guided Few-Shot Anomaly Image-Mask Pair Synthesis for Industrial Inspection
Yilin Lu, Jianghang Lin, Linhuang Xie +5
Anomaly inspection plays a vital role in industrial manufacturing, but the scarcity of anomaly samples significantly limits the effectiveness of existing methods in tasks such as l…
What You Perceive Is What You Conceive: A Cognition-Inspired Framework for Open Vocabulary Image Segmentation
Jianghang Lin, Yue Hu, Jiangtao Shen +4
Open vocabulary image segmentation tackles the challenge of recognizing dynamically adjustable, predefined novel categories at inference time by leveraging vision-language alignmen…