Copertina

RAP: Retrieve, Adapt, and Prompt-Fit for Training-Free Few-Shot Medical Image Segmentation

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Mao, Zhihao, Chen, Bangpu
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Computer Vision and Pattern Recognition Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Few-Shot Medical Image Segmentation with High-Fidelity Prototypes
di: Tang, Song, et al.
Pubblicazione: (2024)

PGP-SAM: Prototype-Guided Prompt Learning for Efficient Few-Shot Medical Image Segmentation
di: Yan, Zhonghao, et al.
Pubblicazione: (2025)

Revealing the Semantic Selection Gap in DINOv3 through Training-Free Few-Shot Segmentation
di: Zakir, Hussni Mohd, et al.
Pubblicazione: (2026)

Zero-Training Task-Specific Model Synthesis for Few-Shot Medical Image Classification
di: Qin, Yao, et al.
Pubblicazione: (2025)

Learnable Prompt for Few-Shot Semantic Segmentation in Remote Sensing Domain
di: Immanuel, Steve Andreas, et al.
Pubblicazione: (2024)

UniFGVC: Universal Training-Free Few-Shot Fine-Grained Vision Classification via Attribute-Aware Multimodal Retrieval
di: Guo, Hongyu, et al.
Pubblicazione: (2025)

Few-Shot Remote Sensing Image Scene Classification with CLIP and Prompt Learning
di: Dimitrovski, Ivica, et al.
Pubblicazione: (2025)

Evolving, Not Training: Zero-Shot Reasoning Segmentation via Evolutionary Prompting
di: Ye, Kai, et al.
Pubblicazione: (2025)

FALCON: Few-Shot Adversarial Learning for Cross-Domain Medical Image Segmentation
di: Fayjie, Abdur R., et al.
Pubblicazione: (2026)

Curriculum Prompting Foundation Models for Medical Image Segmentation
di: Zheng, Xiuqi, et al.
Pubblicazione: (2024)

TP-UNet: Temporal Prompt Guided UNet for Medical Image Segmentation
di: Wang, Ranmin, et al.
Pubblicazione: (2024)

Bidirectional Multimodal Prompt Learning with Scale-Aware Training for Few-Shot Multi-Class Anomaly Detection
di: Lee, Yujin, et al.
Pubblicazione: (2024)

Zero-Shot Industrial Anomaly Segmentation with Image-Aware Prompt Generation
di: Park, SoYoung, et al.
Pubblicazione: (2025)

Beyond Adapting SAM: Towards End-to-End Ultrasound Image Segmentation via Auto Prompting
di: Lin, Xian, et al.
Pubblicazione: (2023)

ProtoSAM: One-Shot Medical Image Segmentation With Foundational Models
di: Ayzenberg, Lev, et al.
Pubblicazione: (2024)

Medical Visual Prompting (MVP): A Unified Framework for Versatile and High-Quality Medical Image Segmentation
di: Chen, Yulin, et al.
Pubblicazione: (2024)

Decoupling Template Bias in CLIP: Harnessing Empty Prompts for Enhanced Few-Shot Learning
di: Zhang, Zhenyu, et al.
Pubblicazione: (2025)

Medical SAM3: A Foundation Model for Universal Prompt-Driven Medical Image Segmentation
di: Jiang, Chongcong, et al.
Pubblicazione: (2026)

Few-Shot Anomaly-Driven Generation for Anomaly Classification and Segmentation
di: Gui, Guan, et al.
Pubblicazione: (2025)

Efficient Masked Attention Transformer for Few-Shot Classification and Segmentation
di: Carrión-Ojeda, Dustin, et al.
Pubblicazione: (2025)

SD-FSMIS: Adapting Stable Diffusion for Few-Shot Medical Image Segmentation
di: Li, Meihua, et al.
Pubblicazione: (2026)

Adapting Foundation Models for Few-Shot Medical Image Segmentation: Actively and Sequentially
di: Yang, Jingyun, et al.
Pubblicazione: (2025)

ProSona: Prompt-Guided Personalization for Multi-Expert Medical Image Segmentation
di: Elgebaly, Aya, et al.
Pubblicazione: (2025)

Med-PerSAM: One-Shot Visual Prompt Tuning for Personalized Segment Anything Model in Medical Domain
di: Yoon, Hangyul, et al.
Pubblicazione: (2024)

Exploring Cross-Domain Few-Shot Classification via Frequency-Aware Prompting
di: Zhang, Tiange, et al.
Pubblicazione: (2024)

TV-SAM: Increasing Zero-Shot Segmentation Performance on Multimodal Medical Images Using GPT-4 Generated Descriptive Prompts Without Human Annotation
di: Jiang, Zekun, et al.
Pubblicazione: (2024)

Lightweight Frequency Masker for Cross-Domain Few-Shot Semantic Segmentation
di: Tong, Jintao, et al.
Pubblicazione: (2024)

The Devil is in Low-Level Features for Cross-Domain Few-Shot Segmentation
di: Liu, Yuhan, et al.
Pubblicazione: (2025)

SRU-Pix2Pix: A Fusion-Driven Generator Network for Medical Image Translation with Few-Shot Learning
di: Qiu, Xihe, et al.
Pubblicazione: (2026)

Training-Free Text-Guided Image Editing with Visual Autoregressive Model
di: Wang, Yufei, et al.
Pubblicazione: (2025)

Self-Attention Diffusion Models for Zero-Shot Biomedical Image Segmentation: Unlocking New Frontiers in Medical Imaging
di: Hamrani, Abderrachid, et al.
Pubblicazione: (2025)

RAP: Retrieval-Augmented Planner for Adaptive Procedure Planning in Instructional Videos
di: Zare, Ali, et al.
Pubblicazione: (2024)

Few Shot Semantic Segmentation: a review of methodologies, benchmarks, and open challenges
di: Catalano, Nico, et al.
Pubblicazione: (2023)

Few-Shot Adaptation of Training-Free Foundation Model for 3D Medical Image Segmentation
di: He, Xingxin, et al.
Pubblicazione: (2025)

DuPLUS: Dual-Prompt Vision-Language Framework for Universal Medical Image Segmentation and Prognosis
di: Saeed, Numan, et al.
Pubblicazione: (2025)

K-Prism: A Knowledge-Guided and Prompt Integrated Universal Medical Image Segmentation Model
di: Guo, Bangwei, et al.
Pubblicazione: (2025)

NubbleDrop: A Simple Way to Improve Matching Strategy for Prompted One-Shot Segmentation
di: Xu, Zhiyu, et al.
Pubblicazione: (2024)

SynPo: Boosting Training-Free Few-Shot Medical Segmentation via High-Quality Negative Prompts
di: Liu, Yufei, et al.
Pubblicazione: (2025)

Chaos-Enhanced Prototypical Networks for Few-Shot Medical Image Classification
di: Sai, Chinthakuntla Meghan, et al.
Pubblicazione: (2026)

Expert-Guided Explainable Few-Shot Learning for Medical Image Diagnosis
di: Uddin, Ifrat Ikhtear, et al.
Pubblicazione: (2025)