22 citations · 31 across the 19 of their papers we have counts for
4 papers · 1 filter
AD-Copilot: A Vision-Language Assistant for Industrial Anomaly Detection via Visual In-context Comparison
Xi Jiang, Yue Guo, Jian Li +7
Multimodal Large Language Models (MLLMs) have achieved impressive success in natural visual understanding, yet they consistently underperform in industrial anomaly detection (IAD).…
Learning Trajectory-Aware Multimodal Large Language Models for Video Reasoning Segmentation
Jingnan Luo, Mingqi Gao, Jun Liu +2
The prosperity of Multimodal Large Language Models (MLLMs) has stimulated the demand for video reasoning segmentation, which aims to segment video objects based on human instructio…
ConsistentRFT: Reducing Visual Hallucinations in Flow-based Reinforcement Fine-Tuning
Xiaofeng Tan, Jun Liu, Yuanting Fan +7
Reinforcement Fine-Tuning (RFT) on flow-based models is crucial for preference alignment. However, they often introduce visual hallucinations like over-optimized details and semant…
One Language-Free Foundation Model Is Enough for Universal Vision Anomaly Detection
Bin-Bin Gao, Chengjie Wang
Universal visual anomaly detection (AD) aims to identify anomaly images and segment anomaly regions towards open and dynamic scenarios, following zero- and few-shot paradigms witho…