:: Library Catalog

Copertina

Salvato in:

Dettagli Bibliografici
Autori principali:	Zhou, Yunyi, Shi, Kun, Hao, Gang
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Computer Vision and Pattern Recognition
Accesso online:	https://arxiv.org/abs/2502.11338
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

SEG-SAM: Semantic-Guided SAM for Unified Medical Image Segmentation
di: Huang, Shuangping, et al.
Pubblicazione: (2024)

3DTeethSAM: Taming SAM2 for 3D Teeth Segmentation
di: Lu, Zhiguo, et al.
Pubblicazione: (2025)

Iris-SAM: Iris Segmentation Using a Foundation Model
di: Farmanifard, Parisa, et al.
Pubblicazione: (2024)

WPS-SAM: Towards Weakly-Supervised Part Segmentation with Foundation Models
di: Wu, Xinjian, et al.
Pubblicazione: (2024)

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

Correspondence as Video: Test-Time Adaption on SAM2 for Reference Segmentation in the Wild
di: Wang, Haoran, et al.
Pubblicazione: (2025)

SAM-IF: Leveraging SAM for Incremental Few-Shot Instance Segmentation
di: Zhou, Xudong, et al.
Pubblicazione: (2024)

From SAM to DINOv2: Towards Distilling Foundation Models to Lightweight Baselines for Generalized Polyp Segmentation
di: Agnihotri, Shivanshu, et al.
Pubblicazione: (2025)

SAM-Driven Weakly Supervised Nodule Segmentation with Uncertainty-Aware Cross Teaching
di: Zhao, Xingyue, et al.
Pubblicazione: (2024)

SAM-PD: How Far Can SAM Take Us in Tracking and Segmenting Anything in Videos by Prompt Denoising
di: Zhou, Tao, et al.
Pubblicazione: (2024)

SAM-MI: A Mask-Injected Framework for Enhancing Open-Vocabulary Semantic Segmentation with SAM
di: Chen, Lin, et al.
Pubblicazione: (2025)

Continual Alignment for SAM: Rethinking Foundation Models for Medical Image Segmentation in Continual Learning
di: Wang, Jiayi, et al.
Pubblicazione: (2025)

A Survey on Segment Anything Model (SAM): Vision Foundation Model Meets Prompt Engineering
di: Zhang, Chaoning, et al.
Pubblicazione: (2023)

pFedSAM: Personalized Federated Learning of Segment Anything Model for Medical Image Segmentation
di: Wang, Tong, et al.
Pubblicazione: (2025)

TextureSAM: Towards a Texture Aware Foundation Model for Segmentation
di: Cohen, Inbal, et al.
Pubblicazione: (2025)

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

AD-SAM: Fine-Tuning the Segment Anything Vision Foundation Model for Autonomous Driving Perception
di: Camarena, Mario, et al.
Pubblicazione: (2025)

Self-Prompt SAM: Medical Image Segmentation via Automatic Prompt SAM Adaptation
di: Xie, Bin, et al.
Pubblicazione: (2025)

Feature Quality and Adaptability of Medical Foundation Models: A Comparative Evaluation for Radiographic Classification and Segmentation
di: Li, Frank, et al.
Pubblicazione: (2025)

Point-SAM: Promptable 3D Segmentation Model for Point Clouds
di: Zhou, Yuchen, et al.
Pubblicazione: (2024)

SAM-aware Test-time Adaptation for Universal Medical Image Segmentation
di: Wu, Jianghao, et al.
Pubblicazione: (2025)

SAM-Mamba: Mamba Guided SAM Architecture for Generalized Zero-Shot Polyp Segmentation
di: Dutta, Tapas Kumar, et al.
Pubblicazione: (2024)

AMA-SAM: Adversarial Multi-Domain Alignment of Segment Anything Model for High-Fidelity Histology Nuclei Segmentation
di: Qian, Jiahe, et al.
Pubblicazione: (2025)

RFMedSAM 2: Automatic Prompt Refinement for Enhanced Volumetric Medical Image Segmentation with SAM 2
di: Xie, Bin, et al.
Pubblicazione: (2025)

From SAM to SAM 2: Exploring Improvements in Meta's Segment Anything Model
di: Geetha, Athulya Sundaresan, et al.
Pubblicazione: (2024)

RobustMedSAM: Degradation-Resilient Medical Image Segmentation via Robust Foundation Model Adaptation
di: Li, Jieru, et al.
Pubblicazione: (2026)

PlantSAM: An Object Detection-Driven Segmentation Pipeline for Herbarium Specimens
di: Sklab, Youcef, et al.
Pubblicazione: (2025)

SAMWISE: Infusing Wisdom in SAM2 for Text-Driven Video Segmentation
di: Cuttano, Claudia, et al.
Pubblicazione: (2024)

MaskSAM: Towards Auto-prompt SAM with Mask Classification for Volumetric Medical Image Segmentation
di: Xie, Bin, et al.
Pubblicazione: (2024)

PolSAM: Polarimetric Scattering Mechanism Informed Segment Anything Model
di: Wang, Yuqing, et al.
Pubblicazione: (2024)

Compress Any Segment Anything Model (SAM)
di: Fan, Juntong, et al.
Pubblicazione: (2025)

Black-box Targeted Adversarial Attack on Segment Anything (SAM)
di: Zheng, Sheng, et al.
Pubblicazione: (2023)

Frequency Adapter with SAM for Generalized Medical Image Segmentation
di: Bui, Phuoc-Nguyen, et al.
Pubblicazione: (2026)

CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation
di: Fu, Yihang, et al.
Pubblicazione: (2024)

Fully Automated SAM for Single-source Domain Generalization in Medical Image Segmentation
di: Zhuo, Huanli, et al.
Pubblicazione: (2025)

SinkSAM-Net: Knowledge-Driven Self-Supervised Sinkhole Segmentation Using Topographic Priors and Segment Anything Model
di: Rafaeli, Osher, et al.
Pubblicazione: (2024)

Interactive 3D Medical Image Segmentation with SAM 2
di: Shen, Chuyun, et al.
Pubblicazione: (2024)

SAM2-UNeXT: An Improved High-Resolution Baseline for Adapting Foundation Models to Downstream Segmentation Tasks
di: Xiong, Xinyu, et al.
Pubblicazione: (2025)

VideoSAM: A Large Vision Foundation Model for High-Speed Video Segmentation
di: Maduabuchi, Chika, et al.
Pubblicazione: (2024)

The SAM2-to-SAM3 Gap in the Segment Anything Model Family: Why Prompt-Based Expertise Fails in Concept-Driven Image Segmentation
di: Sapkota, Ranjan, et al.
Pubblicazione: (2025)