Adapting Visual-Language Models for Generalizable Anomaly Detection in Medical Images
Fuente:
arXiv
Saved in:
| Main Authors: | Huang, Chaoqin, Jiang, Aofan, Feng, Jinghao, Zhang, Ya, Wang, Xinchao, Wang, Yanfeng |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Multi-Scale Memory Comparison for Zero-/Few-Shot Anomaly Detection
by: Huang, Chaoqin, et al.
Published: (2023)
by: Huang, Chaoqin, et al.
Published: (2023)
Few-Shot Anomaly Detection via Category-Agnostic Registration Learning
by: Huang, Chaoqin, et al.
Published: (2024)
by: Huang, Chaoqin, et al.
Published: (2024)
Anomaly Detection in Electrocardiograms: Advancing Clinical Diagnosis Through Self-Supervised Learning
by: Jiang, Aofan, et al.
Published: (2024)
by: Jiang, Aofan, et al.
Published: (2024)
Self-supervised Anomaly Detection Pretraining Enhances Long-tail ECG Diagnosis
by: Jiang, Aofan, et al.
Published: (2024)
by: Jiang, Aofan, et al.
Published: (2024)
Demographic-Aware Self-Supervised Anomaly Detection Pretraining for Equitable Rare Cardiac Diagnosis
by: Huang, Chaoqin, et al.
Published: (2026)
by: Huang, Chaoqin, et al.
Published: (2026)
Language Model as Visual Explainer
by: Yang, Xingyi, et al.
Published: (2024)
by: Yang, Xingyi, et al.
Published: (2024)
M^3Builder: A Multi-Agent System for Automated Machine Learning in Medical Imaging
by: Feng, Jinghao, et al.
Published: (2025)
by: Feng, Jinghao, et al.
Published: (2025)
MoMa: Modulating Mamba for Adapting Image Foundation Models to Video Recognition
by: Yang, Yuhuan, et al.
Published: (2025)
by: Yang, Yuhuan, et al.
Published: (2025)
AdaptCLIP: Adapting CLIP for Universal Visual Anomaly Detection
by: Gao, Bin-Bin, et al.
Published: (2025)
by: Gao, Bin-Bin, et al.
Published: (2025)
MediCLIP: Adapting CLIP for Few-shot Medical Image Anomaly Detection
by: Zhang, Ximiao, et al.
Published: (2024)
by: Zhang, Ximiao, et al.
Published: (2024)
SOWA: Adapting Hierarchical Frozen Window Self-Attention to Visual-Language Models for Better Anomaly Detection
by: Hu, Zongxiang, et al.
Published: (2024)
by: Hu, Zongxiang, et al.
Published: (2024)
PMC-VQA: Visual Instruction Tuning for Medical Visual Question Answering
by: Zhang, Xiaoman, et al.
Published: (2023)
by: Zhang, Xiaoman, et al.
Published: (2023)
Vision-Language Semantic Aggregation Leveraging Foundation Model for Generalizable Medical Image Segmentation
by: Yu, Wenjun, et al.
Published: (2025)
by: Yu, Wenjun, et al.
Published: (2025)
Reprogramming Distillation for Medical Foundation Models
by: Zhou, Yuhang, et al.
Published: (2024)
by: Zhou, Yuhang, et al.
Published: (2024)
Knowledge-enhanced Visual-Language Pretraining for Computational Pathology
by: Zhou, Xiao, et al.
Published: (2024)
by: Zhou, Xiao, et al.
Published: (2024)
Anomaly Detection by Adapting a pre-trained Vision Language Model
by: Cai, Yuxuan, et al.
Published: (2024)
by: Cai, Yuxuan, et al.
Published: (2024)
ChatBEV: A Visual Language Model that Understands BEV Maps
by: Xu, Qingyao, et al.
Published: (2025)
by: Xu, Qingyao, et al.
Published: (2025)
Language Models Meet Anomaly Detection for Better Interpretability and Generalizability
by: Li, Jun, et al.
Published: (2024)
by: Li, Jun, et al.
Published: (2024)
Low-Rank Knowledge Decomposition for Medical Foundation Models
by: Zhou, Yuhang, et al.
Published: (2024)
by: Zhou, Yuhang, et al.
Published: (2024)
Introducing Visual Perception Token into Multimodal Large Language Model
by: Yu, Runpeng, et al.
Published: (2025)
by: Yu, Runpeng, et al.
Published: (2025)
When To Adapt? Adapting the Model or Data in Federated Medical Imaging
by: Shiranthika, Chamani, et al.
Published: (2026)
by: Shiranthika, Chamani, et al.
Published: (2026)
Adapting Foundation Models for Few-Shot Medical Image Segmentation: Actively and Sequentially
by: Yang, Jingyun, et al.
Published: (2025)
by: Yang, Jingyun, et al.
Published: (2025)
ASBench: Image Anomalies Synthesis Benchmark for Anomaly Detection
by: Zhang, Qunyi, et al.
Published: (2025)
by: Zhang, Qunyi, et al.
Published: (2025)
Attention Prompting on Image for Large Vision-Language Models
by: Yu, Runpeng, et al.
Published: (2024)
by: Yu, Runpeng, et al.
Published: (2024)
FAIR: Frequency-aware Image Restoration for Industrial Visual Anomaly Detection
by: Liu, Tongkun, et al.
Published: (2023)
by: Liu, Tongkun, et al.
Published: (2023)
Deep Reprogramming Distillation for Medical Foundation Models
by: Du, Siyuan, et al.
Published: (2026)
by: Du, Siyuan, et al.
Published: (2026)
AdaptPrompt: Parameter-Efficient Adaptation of VLMs for Generalizable Deepfake Detection
by: Jiang, Yichen, et al.
Published: (2025)
by: Jiang, Yichen, et al.
Published: (2025)
PromptMoE: Generalizable Zero-Shot Anomaly Detection via Visually-Guided Prompt Mixtures
by: Shao, Yuheng, et al.
Published: (2025)
by: Shao, Yuheng, et al.
Published: (2025)
Adapt2Reward: Adapting Video-Language Models to Generalizable Robotic Rewards via Failure Prompts
by: Yang, Yanting, et al.
Published: (2024)
by: Yang, Yanting, et al.
Published: (2024)
PhenoLIP: Integrating Phenotype Ontology Knowledge into Medical Vision-Language Pretraining
by: Liang, Cheng, et al.
Published: (2026)
by: Liang, Cheng, et al.
Published: (2026)
Towards Training-free Anomaly Detection with Vision and Language Foundation Models
by: Zhang, Jinjin, et al.
Published: (2025)
by: Zhang, Jinjin, et al.
Published: (2025)
SD-MAD: Sign-Driven Few-shot Multi-Anomaly Detection in Medical Images
by: Guo, Kaiyu, et al.
Published: (2025)
by: Guo, Kaiyu, et al.
Published: (2025)
AnomalyMoE: Towards a Language-free Generalist Model for Unified Visual Anomaly Detection
by: Gu, Zhaopeng, et al.
Published: (2025)
by: Gu, Zhaopeng, et al.
Published: (2025)
Customizing Visual-Language Foundation Models for Multi-modal Anomaly Detection and Reasoning
by: Xu, Xiaohao, et al.
Published: (2024)
by: Xu, Xiaohao, et al.
Published: (2024)
From CNN to CNN + RNN: Adapting Visualization Techniques for Time-Series Anomaly Detection
by: Poirier, Fabien
Published: (2024)
by: Poirier, Fabien
Published: (2024)
Reasoning-Driven Anomaly Detection and Localization with Image-Level Supervision
by: Jin, Yizhou, et al.
Published: (2026)
by: Jin, Yizhou, et al.
Published: (2026)
Fusion of Domain-Adapted Vision and Language Models for Medical Visual Question Answering
by: Ha, Cuong Nhat, et al.
Published: (2024)
by: Ha, Cuong Nhat, et al.
Published: (2024)
Adapting Human Mesh Recovery with Vision-Language Feedback
by: Xu, Chongyang, et al.
Published: (2025)
by: Xu, Chongyang, et al.
Published: (2025)
CoDA: From Text-to-Image Diffusion Models to Training-Free Dataset Distillation
by: Zhou, Letian, et al.
Published: (2025)
by: Zhou, Letian, et al.
Published: (2025)
Dimple: Discrete Diffusion Multimodal Large Language Model with Parallel Decoding
by: Yu, Runpeng, et al.
Published: (2025)
by: Yu, Runpeng, et al.
Published: (2025)
Similar Items
-
Multi-Scale Memory Comparison for Zero-/Few-Shot Anomaly Detection
by: Huang, Chaoqin, et al.
Published: (2023) -
Few-Shot Anomaly Detection via Category-Agnostic Registration Learning
by: Huang, Chaoqin, et al.
Published: (2024) -
Anomaly Detection in Electrocardiograms: Advancing Clinical Diagnosis Through Self-Supervised Learning
by: Jiang, Aofan, et al.
Published: (2024) -
Self-supervised Anomaly Detection Pretraining Enhances Long-tail ECG Diagnosis
by: Jiang, Aofan, et al.
Published: (2024) -
Demographic-Aware Self-Supervised Anomaly Detection Pretraining for Equitable Rare Cardiac Diagnosis
by: Huang, Chaoqin, et al.
Published: (2026)