1 citations · 1 across the 9 of their papers we have counts for
5 papers · 1 filter
DuoAD: Leveraging [CLS] Dual Characteristics for Training-Free Few-Shot Anomaly Detection
Jyun-Ze Tang, Po-Han Huang, Ming-Ching Chang +2
Vision foundation models have enabled strong training-free anomaly detection (AD). However, most existing approaches rely primarily on independent local patch features, leaving the…
How Bias Binds: Measuring Hidden Associations for Bias Control in Text-to-Image Compositions
Jeng-Lin Li, Ming-Ching Chang, Wei-Chao Chen
Text-to-image generative models often exhibit bias related to sensitive attributes. However, current research tends to focus narrowly on single-object prompts with limited contextu…
PatchEAD: Unifying Industrial Visual Prompting Frameworks for Patch-Exclusive Anomaly Detection
Po-Han Huang, Jeng-Lin Li, Po-Hsuan Huang +2
Industrial anomaly detection is increasingly relying on foundation models, aiming for strong out-of-distribution generalization and rapid adaptation in real-world deployments. Nota…
Who Brings the Frisbee: Probing Hidden Hallucination Factors in Large Vision-Language Model via Causality Analysis
Po-Hsuan Huang, Jeng-Lin Li, Chin-Po Chen +2
Recent advancements in large vision-language models (LVLM) have significantly enhanced their ability to comprehend visual inputs alongside natural language. However, a major challe…
Improving Limited Supervised Foot Ulcer Segmentation Using Cross-Domain Augmentation
Shang-Jui Kuo, Po-Han Huang, Chia-Ching Lin +2
Diabetic foot ulcers pose health risks, including higher morbidity, mortality, and amputation rates. Monitoring wound areas is crucial for proper care, but manual segmentation is s…