Copertina

Tuning a SAM-Based Model with Multi-Cognitive Visual Adapter to Remote Sensing Instance Segmentation

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Zheng, Linghao, Pu, Xinyang, Xu, Feng
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Computer Vision and Pattern Recognition
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

ClassWise-SAM-Adapter: Parameter Efficient Fine-tuning Adapts Segment Anything to SAR Domain for Semantic Segmentation
di: Pu, Xinyang, et al.
Pubblicazione: (2024)

Low-Rank Adaption on Transformer-based Oriented Object Detector for Satellite Onboard Processing of Remote Sensing Images
di: Pu, Xinyang, et al.
Pubblicazione: (2024)

ViRefSAM: Visual Reference-Guided Segment Anything Model for Remote Sensing Segmentation
di: Bi, Hanbo, et al.
Pubblicazione: (2025)

Multi-view Remote Sensing Image Segmentation With SAM priors
di: Qi, Zipeng, et al.
Pubblicazione: (2024)

On the Effectiveness of Textual Prompting with Lightweight Fine-Tuning for SAM3 Remote Sensing Segmentation
di: Blushtein-Livnon, Roni, et al.
Pubblicazione: (2025)

PointSAM: Pointly-Supervised Segment Anything Model for Remote Sensing Images
di: Liu, Nanqing, et al.
Pubblicazione: (2024)

Medical SAM Adapter: Adapting Segment Anything Model for Medical Image Segmentation
di: Wu, Junde, et al.
Pubblicazione: (2023)

Insight Any Instance: Promptable Instance Segmentation for Remote Sensing Images
di: Li, Xuexue
Pubblicazione: (2024)

SolarSAM: Building-scale Photovoltaic Potential Assessment Based on Segment Anything Model (SAM) and Remote Sensing for Emerging City
di: Wang, Guohao
Pubblicazione: (2024)

Learning to Aggregate Multi-Scale Context for Instance Segmentation in Remote Sensing Images
di: Liu, Ye, et al.
Pubblicazione: (2021)

Bridging Semantics and Geometry: A Decoupled LVLM-SAM Framework for Reasoning Segmentation in Optical Remote Sensing
di: Zhang, Xu, et al.
Pubblicazione: (2025)

RS2-SAM2: Customized SAM2 for Referring Remote Sensing Image Segmentation
di: Rong, Fu, et al.
Pubblicazione: (2025)

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

Image-Conditioned Instance Prompt Network for Referring Remote Sensing Image Segmentation
di: Ren, Biaoyu, et al.
Pubblicazione: (2026)

RemoteSAM: Towards Segment Anything for Earth Observation
di: Yao, Liang, et al.
Pubblicazione: (2025)

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

Enhancing SAR Object Detection with Self-Supervised Pre-training on Masked Auto-Encoders
di: Pu, Xinyang, et al.
Pubblicazione: (2025)

ROS-SAM: High-Quality Interactive Segmentation for Remote Sensing Moving Object
di: Shan, Zhe, et al.
Pubblicazione: (2025)

SAM2-ELNet: Label Enhancement and Automatic Annotation for Remote Sensing Segmentation
di: Yang, Jianhao, et al.
Pubblicazione: (2025)

ZoRI: Towards Discriminative Zero-Shot Remote Sensing Instance Segmentation
di: Huang, Shiqi, et al.
Pubblicazione: (2024)

SCORE: Scene Context Matters in Open-Vocabulary Remote Sensing Instance Segmentation
di: Huang, Shiqi, et al.
Pubblicazione: (2025)

SOPSeg: Prompt-based Small Object Instance Segmentation in Remote Sensing Imagery
di: Wang, Chenhao, et al.
Pubblicazione: (2025)

Multi-Scale Global-Instance Prompt Tuning for Continual Test-time Adaptation in Medical Image Segmentation
di: Li, Lingrui, et al.
Pubblicazione: (2026)

Semantic-aware SAM for Point-Prompted Instance Segmentation
di: Wei, Zhaoyang, et al.
Pubblicazione: (2023)

InstructSAM: Segment Any Instance with Any Instructions
di: Yuan, Yuqian, et al.
Pubblicazione: (2026)

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

TS-SAM: Fine-Tuning Segment-Anything Model for Downstream Tasks
di: Yu, Yang, et al.
Pubblicazione: (2024)

FusionSAM: Visual Multi-Modal Learning with Segment Anything
di: Li, Daixun, et al.
Pubblicazione: (2024)

UrbanSAM: Learning Invariance-Inspired Adapters for Segment Anything Models in Urban Construction
di: Li, Chenyu, et al.
Pubblicazione: (2025)

Optimal Transport Adapter Tuning for Bridging Modality Gaps in Few-Shot Remote Sensing Scene Classification
di: Ji, Zhong, et al.
Pubblicazione: (2025)

SPDA-SAM: A Self-prompted Depth-Aware Segment Anything Model for Instance Segmentation
di: Shang, Yihan, et al.
Pubblicazione: (2026)

S^4M: Boosting Semi-Supervised Instance Segmentation with SAM
di: Yoon, Heeji, et al.
Pubblicazione: (2025)

SAM-guided Graph Cut for 3D Instance Segmentation
di: Guo, Haoyu, et al.
Pubblicazione: (2023)

PA-SAM: Prompt Adapter SAM for High-Quality Image Segmentation
di: Xie, Zhaozhi, et al.
Pubblicazione: (2024)

AMMUNet: Multi-Scale Attention Map Merging for Remote Sensing Image Segmentation
di: Yang, Yang, et al.
Pubblicazione: (2024)

AerOSeg: Harnessing SAM for Open-Vocabulary Segmentation in Remote Sensing Images
di: Dutta, Saikat, et al.
Pubblicazione: (2025)

ReSAM: Refine, Requery, and Reinforce: Self-Prompting Point-Supervised Segmentation for Remote Sensing Images
di: Subhani, M. Naseer
Pubblicazione: (2025)

SAM3-Adapter: Efficient Adaptation of Segment Anything 3 for Camouflage Object Segmentation, Shadow Detection, and Medical Image Segmentation
di: Chen, Tianrun, et al.
Pubblicazione: (2025)

SAM-PTx: Text-Guided Fine-Tuning of SAM with Parameter-Efficient, Parallel-Text Adapters
di: Jalilian, Shayan, et al.
Pubblicazione: (2025)

Evaluation Study on SAM 2 for Class-agnostic Instance-level Segmentation
di: Pei, Jialun, et al.
Pubblicazione: (2024)