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Related papers: Segment Anything

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Segment Anything (SAM) has recently pushed the boundaries of segmentation by demonstrating zero-shot generalization and flexible prompting after training on over one billion masks. Despite this, its mask prediction accuracy often falls…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Zezhong Fan , Xiaohan Li , Topojoy Biswas , Kaushiki Nag , Kannan Achan

The Segment Anything Model (SAM), introduced to the computer vision community by Meta in April 2023, is a groundbreaking tool that allows automated segmentation of objects in images based on prompts such as text, clicks, or bounding boxes.…

Computer Vision and Pattern Recognition · Computer Science 2024-08-13 Athulya Sundaresan Geetha , Muhammad Hussain

Recently, Meta AI Research approaches a general, promptable Segment Anything Model (SAM) pre-trained on an unprecedentedly large segmentation dataset (SA-1B). Without a doubt, the emergence of SAM will yield significant benefits for a wide…

Computer Vision and Pattern Recognition · Computer Science 2024-08-23 Wei Ji , Jingjing Li , Qi Bi , Tingwei Liu , Wenbo Li , Li Cheng

Segment Anything Model (SAM) has achieved impressive results for natural image segmentation with input prompts such as points and bounding boxes. Its success largely owes to massive labeled training data. However, directly applying SAM to…

Image and Video Processing · Electrical Eng. & Systems 2023-11-21 Jin Ye , Junlong Cheng , Jianpin Chen , Zhongying Deng , Tianbin Li , Haoyu Wang , Yanzhou Su , Ziyan Huang , Jilong Chen , Lei Jiang , Hui Sun , Min Zhu , Shaoting Zhang , Junjun He , Yu Qiao

The recent Segment Anything Model (SAM) represents a big leap in scaling up segmentation models, allowing for powerful zero-shot capabilities and flexible prompting. Despite being trained with 1.1 billion masks, SAM's mask prediction…

Computer Vision and Pattern Recognition · Computer Science 2023-10-24 Lei Ke , Mingqiao Ye , Martin Danelljan , Yifan Liu , Yu-Wing Tai , Chi-Keung Tang , Fisher Yu

The segment anything model (SAM) was released as a foundation model for image segmentation. The promptable segmentation model was trained by over 1 billion masks on 11M licensed and privacy-respecting images. The model supports zero-shot…

Recently, the first foundation model developed specifically for image segmentation tasks was developed, termed the "Segment Anything Model" (SAM). SAM can segment objects in input imagery based on cheap input prompts, such as one (or more)…

Computer Vision and Pattern Recognition · Computer Science 2023-11-10 Simiao Ren , Francesco Luzi , Saad Lahrichi , Kaleb Kassaw , Leslie M. Collins , Kyle Bradbury , Jordan M. Malof

The Segment Anything Model (SAM) is a new image segmentation tool trained with the largest available segmentation dataset. The model has demonstrated that, with prompts, it can create high-quality masks for general images. However, the…

Image and Video Processing · Electrical Eng. & Systems 2024-02-06 Yihao Liu , Jiaming Zhang , Zhangcong She , Amir Kheradmand , Mehran Armand

Segment Anything (SAM), an advanced universal image segmentation model trained on an expansive visual dataset, has set a new benchmark in image segmentation and computer vision. However, it faced challenges when it came to distinguishing…

Computer Vision and Pattern Recognition · Computer Science 2025-08-27 Xiao Feng Zhang , Tian Yi Song , Jia Wei Yao

Segment Anything Model (SAM) has emerged as a powerful tool for numerous vision applications. A key component that drives the impressive performance for zero-shot transfer and high versatility is a super large Transformer model trained on…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Yunyang Xiong , Bala Varadarajan , Lemeng Wu , Xiaoyu Xiang , Fanyi Xiao , Chenchen Zhu , Xiaoliang Dai , Dilin Wang , Fei Sun , Forrest Iandola , Raghuraman Krishnamoorthi , Vikas Chandra

The Segment Anything Model (SAM) is a recently developed large model for general-purpose segmentation for computer vision tasks. SAM was trained using 11 million images with over 1 billion masks and can produce segmentation results for a…

Computer Vision and Pattern Recognition · Computer Science 2023-06-22 Yizhe Zhang , Tao Zhou , Shuo Wang , Peixian Liang , Danny Z. Chen

The Segment Anything Model (SAM) is the first foundation model for general image segmentation. It has achieved impressive results on various natural image segmentation tasks. However, medical image segmentation (MIS) is more challenging…

Image and Video Processing · Electrical Eng. & Systems 2024-01-18 Yuhao Huang , Xin Yang , Lian Liu , Han Zhou , Ao Chang , Xinrui Zhou , Rusi Chen , Junxuan Yu , Jiongquan Chen , Chaoyu Chen , Sijing Liu , Haozhe Chi , Xindi Hu , Kejuan Yue , Lei Li , Vicente Grau , Deng-Ping Fan , Fajin Dong , Dong Ni

Segmentation is an essential step for remote sensing image processing. This study aims to advance the application of the Segment Anything Model (SAM), an innovative image segmentation model by Meta AI, in the field of remote sensing image…

Computer Vision and Pattern Recognition · Computer Science 2023-11-02 Lucas Prado Osco , Qiusheng Wu , Eduardo Lopes de Lemos , Wesley Nunes Gonçalves , Ana Paula Marques Ramos , Jonathan Li , José Marcato Junior

Meta AI Research has recently released SAM (Segment Anything Model) which is trained on a large segmentation dataset of over 1 billion masks. As a foundation model in the field of computer vision, SAM (Segment Anything Model) has gained…

Computer Vision and Pattern Recognition · Computer Science 2023-05-02 Dongsheng Han , Chaoning Zhang , Yu Qiao , Maryam Qamar , Yuna Jung , SeungKyu Lee , Sung-Ho Bae , Choong Seon Hong

The advent of foundation models signals a new era in artificial intelligence. The Segment Anything Model (SAM) is the first foundation model for image segmentation. In this study, we evaluate SAM's ability to segment features from eye…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Virmarie Maquiling , Sean Anthony Byrne , Diederick C. Niehorster , Marcus Nyström , Enkelejda Kasneci

Segment Anything Model (SAM), a new AI model from Meta AI released in April 2023, is an ambitious tool designed to identify and separate individual objects within a given image through semantic interpretation. The advanced capabilities of…

Image and Video Processing · Electrical Eng. & Systems 2024-11-06 Gabriel Bellon de Carvalho , Jurandy Almeida

We present Segment Anything Model 2 (SAM 2), a foundation model towards solving promptable visual segmentation in images and videos. We build a data engine, which improves model and data via user interaction, to collect the largest video…

The Segment Anything Model (SAM), developed by Meta AI Research, represents a significant breakthrough in computer vision, offering a robust framework for image and video segmentation. This survey provides a comprehensive exploration of the…

The Segment Anything Model (SAM) is a deep neural network foundational model designed to perform instance segmentation which has gained significant popularity given its zero-shot segmentation ability. SAM operates by generating masks based…

Computer Vision and Pattern Recognition · Computer Science 2024-04-19 Yona Falinie A. Gaus , Neelanjan Bhowmik , Brian K. S. Isaac-Medina , Toby P. Breckon

Artificial intelligence (AI) is evolving towards artificial general intelligence, which refers to the ability of an AI system to perform a wide range of tasks and exhibit a level of intelligence similar to that of a human being. This is in…

Computer Vision and Pattern Recognition · Computer Science 2023-05-22 Chunhui Zhang , Li Liu , Yawen Cui , Guanjie Huang , Weilin Lin , Yiqian Yang , Yuehong Hu
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