Copertina

RefSAM: Efficiently Adapting Segmenting Anything Model for Referring Video Object Segmentation

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Li, Yonglin, Zhang, Jing, Teng, Xiao, Lan, Long, Liu, Xinwang
Natura:	Preprint
Pubblicazione:	2023
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

RefSAM3D: Adapting SAM with Cross-modal Reference for 3D Medical Image Segmentation
di: Gao, Xiang, et al.
Pubblicazione: (2024)

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

X-SAM: From Segment Anything to Any Segmentation
di: Wang, Hao, et al.
Pubblicazione: (2025)

Ref-AVS: Refer and Segment Objects in Audio-Visual Scenes
di: Wang, Yaoting, et al.
Pubblicazione: (2024)

Semantic Localization Guiding Segment Anything Model For Reference Remote Sensing Image Segmentation
di: Li, Shuyang, et al.
Pubblicazione: (2025)

SAM 2: Segment Anything in Images and Videos
di: Ravi, Nikhila, et al.
Pubblicazione: (2024)

CamSAM2: Segment Anything Accurately in Camouflaged Videos
di: Zhou, Yuli, et al.
Pubblicazione: (2025)

SAM 3: Segment Anything with Concepts
di: Carion, Nicolas, et al.
Pubblicazione: (2025)

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

Region-Guided Attack on the Segment Anything Model (SAM)
di: Liu, Xiaoliang, et al.
Pubblicazione: (2024)

SparseSAM: Structured Sparsification of Activations in Segment Anything Models
di: Tran, Hoai-Chau, et al.
Pubblicazione: (2026)

Adapting Segment Anything Model to Melanoma Segmentation in Microscopy Slide Images
di: Liu, Qingyuan, et al.
Pubblicazione: (2024)

MedSAM3: Delving into Segment Anything with Medical Concepts
di: Liu, Anglin, et al.
Pubblicazione: (2025)

Q-SAM2: Accurate Quantization for Segment Anything Model 2
di: Farronato, Nicola, et al.
Pubblicazione: (2025)

EfficientViT-SAM: Accelerated Segment Anything Model Without Accuracy Loss
di: Zhang, Zhuoyang, et al.
Pubblicazione: (2024)

SGP-SAM: Self-Gated Prompting for Transferring 3D Segment Anything Models to Lesion Segmentation
di: Tang, Zixuan, et al.
Pubblicazione: (2026)

DeiSAM: Segment Anything with Deictic Prompting
di: Shindo, Hikaru, et al.
Pubblicazione: (2024)

WeakSAM: Segment Anything Meets Weakly-supervised Instance-level Recognition
di: Zhu, Lianghui, 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)

X2SAM: Any Segmentation in Images and Videos
di: Wang, Hao, et al.
Pubblicazione: (2026)

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

Surgical SAM 2: Real-time Segment Anything in Surgical Video by Efficient Frame Pruning
di: Liu, Haofeng, et al.
Pubblicazione: (2024)

Zero-Shot Segmentation of Eye Features Using the Segment Anything Model (SAM)
di: Maquiling, Virmarie, et al.
Pubblicazione: (2023)

MPG-SAM 2: Adapting SAM 2 with Mask Priors and Global Context for Referring Video Object Segmentation
di: Rong, Fu, et al.
Pubblicazione: (2025)

Segment Anything for Videos: A Systematic Survey
di: Zhang, Chunhui, et al.
Pubblicazione: (2024)

MedSAM2: Segment Anything in 3D Medical Images and Videos
di: Ma, Jun, et al.
Pubblicazione: (2025)

ClickSAM: Fine-tuning Segment Anything Model using click prompts for ultrasound image segmentation
di: Guo, Aimee, et al.
Pubblicazione: (2024)

RobustSAM: Segment Anything Robustly on Degraded Images
di: Chen, Wei-Ting, et al.
Pubblicazione: (2024)

MGD-SAM2: Multi-view Guided Detail-enhanced Segment Anything Model 2 for High-Resolution Class-agnostic Segmentation
di: Shen, Haoran, et al.
Pubblicazione: (2025)

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

Eye image segmentation using visual and concept prompts with Segment Anything Model 3 (SAM3)
di: Niehorster, Diederick C., et al.
Pubblicazione: (2026)

Re-purposing SAM into Efficient Visual Projectors for MLLM-Based Referring Image Segmentation
di: Yang, Xiaobo, et al.
Pubblicazione: (2025)

Mitigating Query Selection Bias in Referring Video Object Segmentation
di: Zhang, Dingwei, et al.
Pubblicazione: (2025)

fabSAM: A Farmland Boundary Delineation Method Based on the Segment Anything Model
di: Xie, Yufeng, et al.
Pubblicazione: (2025)

1st Place Solution for 5th LSVOS Challenge: Referring Video Object Segmentation
di: Luo, Zhuoyan, et al.
Pubblicazione: (2024)

BiSeg-SAM: Weakly-Supervised Post-Processing Framework for Boosting Binary Segmentation in Segment Anything Models
di: Su, Encheng, et al.
Pubblicazione: (2025)

Promoting Segment Anything Model towards Highly Accurate Dichotomous Image Segmentation
di: Liu, Xianjie, et al.
Pubblicazione: (2023)

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

EfficientSAM3: Progressive Hierarchical Distillation for Video Concept Segmentation from SAM1, 2, and 3
di: Zeng, Chengxi, et al.
Pubblicazione: (2025)

Efficient Prompt Tuning of Large Vision-Language Model for Fine-Grained Ship Classification
di: Lan, Long, et al.
Pubblicazione: (2024)