:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Mo, Di, Sun, Mingyang, Yin, Chengxiu, Tian, Runjia, Wu, Yanhong, Xu, Liyan
Format:	Preprint
Published:	2026
Subjects:	Computer Vision and Pattern Recognition
Online Access:	https://arxiv.org/abs/2602.07057
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Matte Anything: Interactive Natural Image Matting with Segment Anything Models
by: Yao, Jingfeng, et al.
Published: (2023)

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

VMem: Consistent Interactive Video Scene Generation with Surfel-Indexed View Memory
by: Li, Runjia, et al.
Published: (2025)

Matching Anything by Segmenting Anything
by: Li, Siyuan, et al.
Published: (2024)

UV-SAM: Adapting Segment Anything Model for Urban Village Identification
by: Zhang, Xin, et al.
Published: (2024)

Generalized Few-shot 3D Point Cloud Segmentation with Vision-Language Model
by: An, Zhaochong, et al.
Published: (2025)

Register Anything: Estimating "Corresponding Prompts" for Segment Anything Model
by: Huang, Shiqi, et al.
Published: (2025)

Segment Anything, Even Occluded
by: Tai, Wei-En, et al.
Published: (2025)

MESA: Matching Everything by Segmenting Anything
by: Zhang, Yesheng, et al.
Published: (2024)

Move Anything with Layered Scene Diffusion
by: Ren, Jiawei, et al.
Published: (2024)

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

SAMSA 2.0: Prompting Segment Anything with Spectral Angles for Hyperspectral Interactive Medical Image Segmentation
by: Roddan, Alfie, et al.
Published: (2025)

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

S4M: 4-points to Segment Anything
by: Meyer, Adrien, et al.
Published: (2025)

Boosting Segment Anything Model Towards Open-Vocabulary Learning
by: Han, Xumeng, et al.
Published: (2023)

Segment Anything without Supervision
by: Wang, XuDong, et al.
Published: (2024)

SAMSA: Segment Anything Model Enhanced with Spectral Angles for Hyperspectral Interactive Medical Image Segmentation
by: Roddan, Alfie, et al.
Published: (2025)

Segment Anything in 3D with Radiance Fields
by: Cen, Jiazhong, et al.
Published: (2023)

Segment and Caption Anything
by: Huang, Xiaoke, et al.
Published: (2023)

Hi-SAM: Marrying Segment Anything Model for Hierarchical Text Segmentation
by: Ye, Maoyuan, et al.
Published: (2024)

OmniSAM: Omnidirectional Segment Anything Model for UDA in Panoramic Semantic Segmentation
by: Zhong, Ding, et al.
Published: (2025)

Deshadow-Anything: When Segment Anything Model Meets Zero-shot shadow removal
by: Zhang, Xiao Feng, et al.
Published: (2023)

Segment Anything Model for Grain Characterization in Hard Drive Design
by: Nichols, Kai, et al.
Published: (2024)

Multimodality Helps Few-shot 3D Point Cloud Semantic Segmentation
by: An, Zhaochong, et al.
Published: (2024)

Deep Instruction Tuning for Segment Anything Model
by: Huang, Xiaorui, et al.
Published: (2024)

Efficient Cutting Tool Wear Segmentation Based on Segment Anything Model
by: Li, Zongshuo, et al.
Published: (2024)

Parameter Efficient Fine-tuning via Cross Block Orchestration for Segment Anything Model
by: Peng, Zelin, et al.
Published: (2023)

Continual Learning for Segment Anything Model Adaptation
by: Yang, Jinglong, et al.
Published: (2024)

Latent Diffusion, Implicit Amplification: Efficient Continuous-Scale Super-Resolution for Remote Sensing Images
by: Wu, Hanlin, et al.
Published: (2024)

Segment Anything with Multiple Modalities
by: Xiao, Aoran, et al.
Published: (2024)

Segment Anything for Cell Tracking
by: Chen, Zhu, et al.
Published: (2025)

On Efficient Variants of Segment Anything Model: A Survey
by: Sun, Xiaorui, et al.
Published: (2024)

Zero-Shot Surgical Tool Segmentation in Monocular Video Using Segment Anything Model 2
by: Lou, Ange, et al.
Published: (2024)

CLIP as RNN: Segment Countless Visual Concepts without Training Endeavor
by: Sun, Shuyang, et al.
Published: (2023)

SAM-REF: Introducing Image-Prompt Synergy during Interaction for Detail Enhancement in the Segment Anything Model
by: Yu, Chongkai, et al.
Published: (2024)

Perceive Anything: Recognize, Explain, Caption, and Segment Anything in Images and Videos
by: Lin, Weifeng, et al.
Published: (2025)

SPLF-SAM: Self-Prompting Segment Anything Model for Light Field Salient Object Detection
by: Xu, Qiyao, et al.
Published: (2025)

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

Segment Anything Model is a Good Teacher for Local Feature Learning
by: Wu, Jingqian, et al.
Published: (2023)

Segment Anything Model Can Not Segment Anything: Assessing AI Foundation Model's Generalizability in Permafrost Mapping
by: Li, Wenwen, et al.
Published: (2024)