Welcome to summit your project [here]
- SAM Survey: Chunhui Zhang, Li Liu, Yawen Cui, Guanjie Huang, Weilin Lin, Yiqian Yang, Yuehong Hu.
"A Comprehensive Survey on Segment Anything Model for Vision and Beyond." ArXiv (2023). [paper] [homepage]
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SAM: Alexander Kirillov, Eric Mintun, Nikhila Ravi, Hanzi Mao, Chloe Rolland, Laura Gustafson, Tete Xiao, Spencer Whitehead, Alexander C. Berg, Wan-Yen Lo, Piotr Dollár, Ross Girshick.
"Segment Anything." ArXiv (2023). [paper] [homepage] [code] -
SEEM: Xueyan Zou, Jianwei Yang, Hao Zhang, Feng Li, Linjie Li, Jianfeng Gao, Yong Jae Lee.
"Segment Everything Everywhere All at Once." ArXiv (2023). [paper] [code] -
SegGPT: Xinlong Wang, Xiaosong Zhang, Yue Cao, Wen Wang, Chunhua Shen, Tiejun Huang.
"SegGPT: Segmenting Everything In Context." ArXiv (2023). [paper] [code] -
Grounding DINO: Shilong Liu, Zhaoyang Zeng, Tianhe Ren, Feng Li, Hao Zhang, Jie Yang, Chunyuan Li, Jianwei Yang, Hang Su, Jun Zhu, Lei Zhang.
"Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection." ArXiv (2023). [paper] [code] -
OVSeg: Feng Liang, Bichen Wu, Xiaoliang Dai, Kunpeng Li, Yinan Zhao, Hang Zhang, Peizhao Zhang, Peter Vajda, Diana Marculescu.
"Open-Vocabulary Semantic Segmentation with Mask-adapted CLIP." CVPR (2023). [paper] [homepage] [code] -
OneFormer: Jitesh Jain, Jiachen Li, MangTik Chiu, Ali Hassani, Nikita Orlov, Humphrey Shi.
"OneFormer: One Transformer to Rule Universal Image Segmentation." CVPR (2023). [paper] [homepage] [code] -
ImageBind: Rohit Girdhar, Alaaeldin El-Nouby, Zhuang Liu, Mannat Singh, Kalyan Vasudev Alwala, Armand Joulin, Ishan Misra.
"ImageBind: One Embedding Space To Bind Them All." CVPR (2023). [paper] [homepage] [code]
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SAD: Jun Cen, Yizheng Wu, Kewei Wang, Xingyi Li, Jingkang Yang, Yixuan Pei, Lingdong Kong, Ziwei Liu, Qifeng Chen.
"SAD: Segment Any RGBD." ArXiv (2023). [paper] [code] -
SPT: Zeyu Xiao, Jiawang Bai, Zhihe Lu, Zhiwei Xiong.
"A Dive into SAM Prior in Image Restoration." ArXiv (2023). [paper] -
Matcher: Yang Liu, Muzhi Zhu, Hengtao Li, Hao Chen, Xinlong Wang, Chunhua Shen.
"Matcher: Segment Anything with One Shot Using All-Purpose Feature Matching." ArXiv (2023). [paper] [code] -
RAP: Jiaxi Jiang, Christian Holz.
"Restore Anything Pipeline: Segment Anything Meets Image Restoration." ArXiv (2023). [paper] [code] -
UVOSAM: Zhenghao Zhang, Zhichao Wei, Shengfan Zhang, Zuozhuo Dai, Siyu Zhu.
"UVOSAM: A Mask-free Paradigm for Unsupervised Video Object Segmentation via Segment Anything Model." ArXiv (2023). [paper] -
BreastSAM: Mingzhe Hu, Yuheng Li, Xiaofeng Yang.
"BreastSAM: A Study of Segment Anything Model for Breast Tumor Detection in Ultrasound Images." ArXiv (2023). [paper] -
SAMSh: Leiping Jie, Hui Zhang.
"When SAM Meets Shadow Detection." ArXiv (2023). [paper] [code] -
Instruct2Act: Siyuan Huang, Zhengkai Jiang, Hao Dong, Yu Qiao, Peng Gao, Hongsheng Li.
"Instruct2Act: Mapping Multi-modality Instructions to Robotic Actions with Large Language Model." ArXiv (2023). [paper] [code] -
WS-SAM: Chunming He, Kai Li, Yachao Zhang, Guoxia Xu, Longxiang Tang, Yulun Zhang, Zhenhua Guo, Xiu Li.
"Weakly-Supervised Concealed Object Segmentation with SAM-based Pseudo Labeling and Multi-scale Feature Grouping." ArXiv (2023). [paper] -
SAA+: Yunkang Cao, Xiaohao Xu, Chen Sun, Yuqi Cheng, Zongwei Du, Liang Gao, Weiming Shen.
"Segment Any Anomaly without Training via Hybrid Prompt Regularization." ArXiv (2023). [paper] [code] -
OR-NeRF: Youtan Yin, Zhoujie Fu, Fan Yang, Guosheng Lin.
"OR-NeRF: Object Removing from 3D Scenes Guided by Multiview Segmentation with Neural Radiance Fields." ArXiv (2023). [paper] -
PromptUNet: Junde Wu.
"PromptUNet: Toward Interactive Medical Image Segmentation." ArXiv (2023). [paper] [code] -
EAC: Ao Sun, Pingchuan Ma, Yuanyuan Yuan, Shuai Wang.
"Explain Any Concept: Segment Anything Meets Concept-Based Explanation." ArXiv (2023). [paper] -
Xiao Yang, Haixing Dai, Zihao Wu, Ramesh Bist, Sachin Subedi, Jin Sun, Guoyu Lu, Changying Li, Tianming Liu, Lilong Chai.
"SAM for Poultry Science." ArXiv (2023). [paper] -
Leaf Only SAM: Dominic Williams, Fraser MacFarlane, Avril Britten.
"Leaf Only SAM: A Segment Anything Pipeline for Zero-Shot Automated Leaf Segmentation." ArXiv (2023). [paper] -
KD-SAM: Sahib Julka, Michael Granitzer.
"Knowledge distillation with Segment Anything (SAM) model for Planetary Geological Mapping." ArXiv (2023). [paper] -
SAM-Track: Yangming Cheng, Liulei Li, Yuanyou Xu, Xiaodi Li, Zongxin Yang, Wenguan Wang, Yi Yang.
"Segment-and-Track Anything." ArXiv (2023). [paper] [code] -
SEEM: Zhihe Lu, Zeyu Xiao, Jiawang Bai, Zhiwei Xiong, Xinchao Wang.
"Can SAM Boost Video Super-Resolution?" ArXiv (2023). [paper] -
Yuqing Wang, Yun Zhao, Linda Petzold.
"An Empirical Study on the Robustness of the Segment Anything Model (SAM)." ArXiv (2023). [paper] -
SAM-WSSS: Tianle Chen, Zheda Mai, Ruiwen Li, Wei-lun Chao.
"Segment Anything Model (SAM) Enhanced Pseudo Labels for Weakly Supervised Semantic Segmentation." ArXiv (2023). [paper] [code] -
SAM4MIS: Yichi Zhang, Rushi Jiao.
"How Segment Anything Model (SAM) Boost Medical Image Segmentation?" ArXiv (2023). [paper] [code] -
BadSAM: Zihan Guan, Mengxuan Hu, Zhongliang Zhou, Jielu Zhang, Sheng Li, Ninghao Liu.
"BadSAM: Exploring Security Vulnerabilities of SAM via Backdoor Attacks." ArXiv (2023). [paper] -
PerSAM: Renrui Zhang, Zhengkai Jiang, Ziyu Guo, Shilin Yan, Junting Pan, Hao Dong, Peng Gao, Hongsheng Li.
"Personalize Segment Anything Model with One Shot." ArXiv (2023). [paper] [code] -
CAT: Teng Wang, Jinrui Zhang, Junjie Fei, Hao Zheng, Yunlong Tang, Zhe Li, Mingqi Gao, Shanshan Zhao.
"Caption Anything: Interactive Image Description with Diverse Multimodal Controls." ArXiv (2023). [paper] [code] -
SAMRS: Di Wang, Jing Zhang, Bo Du, Dacheng Tao, Liangpei Zhang.
"Scaling-up Remote Sensing Segmentation Dataset with Segment Anything Model." ArXiv (2023). [paper] [code] -
AV-SAM: Shentong Mo, Yapeng Tian.
"AV-SAM: Segment Anything Model Meets Audio-Visual Localization and Segmentation." ArXiv (2023). [paper] -
WSSS: Weixuan Sun, Zheyuan Liu, Yanhao Zhang, Yiran Zhong, Nick Barnes.
"An Alternative to WSSS? An Empirical Study of the Segment Anything Model (SAM) on Weakly-Supervised Semantic Segmentation Problems." ArXiv (2023). [paper] -
PLG-SAM: Peng-Tao Jiang, Yuqi Yang.
"Segment Anything is A Good Pseudo-label Generator for Weakly Supervised Semantic Segmentation." ArXiv (2023). [paper] -
Attack-SAM: Chenshuang Zhang, Chaoning Zhang, Taegoo Kang, Donghun Kim, Sung-Ho Bae, In So Kweon.
"Attack-SAM: Towards Attacking Segment Anything Model With Adversarial Examples." ArXiv (2023). [paper] -
Polyp-SAM: Yuheng Li, Mingzhe Hu, Xiaofeng Yang.
"Polyp-SAM: Transfer SAM for Polyp Segmentation." ArXiv (2023). [paper] [code] -
Dongsheng Han, Chaoning Zhang, Yu Qiao, Maryam Qamar, Yuna Jung, SeungKyu Lee, Sung-Ho Bae, Choong Seon Hong.
"Segment Anything Model (SAM) Meets Glass: Mirror and Transparent Objects Cannot Be Easily Detected." ArXiv (2023). [paper] -
DSEC-MOS: Zhuyun Zhou, Zongwei Wu, Rémi Boutteau, Fan Yang, Dominique Ginhac.
"DSEC-MOS: Segment Any Moving Object with Moving Ego Vehicle." ArXiv (2023). [paper] [code] -
Christian Mattjie, Luis Vinicius de Moura, Rafaela Cappelari Ravazio, Lucas Silveira Kupssinskü, Otávio Parraga, Marcelo Mussi Delucis, Rodrigo Coelho Barros.
"Zero-shot performance of the Segment Anything Model (SAM) in 2D medical imaging: A comprehensive evaluation and practical guidelines." ArXiv (2023). [paper] [code] -
Dongjie Cheng, Ziyuan Qin, Zekun Jiang, Shaoting Zhang, Qicheng Lao, Kang Li.
"SAM on Medical Images: A Comprehensive Study on Three Prompt Modes." ArXiv (2023). [paper] -
An Wang, Mobarakol Islam, Mengya Xu, Yang Zhang, Hongliang Ren.
"SAM Meets Robotic Surgery: An Empirical Study in Robustness Perspective." ArXiv (2023). [paper] -
Yuhao Huang, Xin Yang, Lian Liu, Han Zhou, Ao Chang, Xinrui Zhou, Rusi Chen, Junxuan Yu, Jiongquan Chen, Chaoyu Chen, Haozhe Chi, Xindi Hu, Deng-Ping Fan, Fajin Dong, Dong Ni.
"Segment Anything Model for Medical Images?" ArXiv (2023). [paper] -
Edit Everything: Defeng Xie, Ruichen Wang, Jian Ma, Chen Chen, Haonan Lu, Dong Yang, Fobo Shi, Xiaodong Lin.
"Edit Everything: A Text-Guided Generative System for Images Editing." ArXiv (2023). [paper] [code] -
SkinSAM: Mingzhe Hu, Yuheng Li, Xiaofeng Yang.
"SkinSAM: Empowering Skin Cancer Segmentation with Segment Anything Model." ArXiv (2023). [paper] -
GazeSAM: Bin Wang, Armstrong Aboah, Zheyuan Zhang, Ulas Bagci.
" GazeSAM: What You See is What You Segment." ArXiv (2023). [paper] [code] -
SAMed: Kaidong Zhang, Dong Liu.
" Customized Segment Anything Model for Medical Image Segmentation." ArXiv (2023). [paper] [code] -
LearnablePromptSAM: Zhongxi Qiu, Yan Hu, Heng Li, Jiang Liu.
" Learnable Ophthalmology SAM." ArXiv (2023). [paper] [code] -
Simiao Ren, Francesco Luzi, Saad Lahrichi, Kaleb Kassaw, Leslie M. Collins, Kyle Bradbury, Jordan M. Malof.
" Segment anything, from space?." ArXiv (2023). [paper] -
Peilun Shi, Jianing Qiu, Sai Mu Dalike Abaxi, Hao Wei, Frank P. -W. Lo, Wu Yuan.
"Generalist Vision Foundation Models for Medical Imaging: A Case Study of Segment Anything Model on Zero-Shot Medical Segmentation." ArXiv (2023). [paper] -
MSA: Junde Wu, Yu Zhang, Rao Fu, Huihui Fang, Yuanpei Liu, Zhaowei Wang, Yanwu Xu, Yueming Jin.
" Medical SAM Adapter: Adapting Segment Anything Model for Medical Image Segmentation." ArXiv (2023). [paper] [code] -
Mohsen Ahmadi, Ahmad Gholizadeh Lonbar, Abbas Sharifi, Ali Tarlani Beris, Mohammadsadegh Nouri, Amir Sharifzadeh Javidi.
"Application of Segment Anything Model for Civil Infrastructure Defect Assessment." ArXiv (2023). [paper] -
SA3D: Jiazhong Cen, Zanwei Zhou, Jiemin Fang, Wei Shen, Lingxi Xie, Dongsheng Jiang, Xiaopeng Zhang, Qi Tian.
" Segment Anything in 3D with NeRFs." ArXiv (2023). [paper] [code] -
MedSAM: Jun Ma, Bo Wang.
" Segment Anything in Medical Images." ArXiv (2023). [paper] [code] -
TAM: Jinyu Yang, Mingqi Gao, Zhe Li, Shang Gao, Fangjing Wang, Feng Zheng.
"Track Anything: Segment Anything Meets Videos." ArXiv (2023). [paper] [code] -
SNA: Yongcheng Jing, Xinchao Wang, Dacheng Tao.
"Segment Anything in Non-Euclidean Domains: Challenges and Opportunities." ArXiv (2023). [paper] -
SAMAug: Yizhe Zhang, Tao Zhou, Peixian Liang, Danny Z. Chen.
"Input Augmentation with SAM: Boosting Medical Image Segmentation with Segmentation Foundation Model." ArXiv (2023). [paper] -
Count-Anything: Zhiheng Ma, Xiaopeng Hong, Qinnan Shangguan.
"Can SAM Count Anything? An Empirical Study on SAM Counting." ArXiv (2023). [paper] [code] -
Text2Seg: Jielu Zhang, Zhongliang Zhou, Gengchen Mai, Lan Mu, Mengxuan Hu, Sheng Li.
" Text2Seg: Remote Sensing Image Semantic Segmentation via Text-Guided Visual Foundation Models." ArXiv (2023). [paper] [code] -
Maciej A. Mazurowski, Haoyu Dong, Hanxue Gu, Jichen Yang, Nicholas Konz, Yixin Zhang.
"Segment Anything Model for Medical Image Analysis: an Experimental Study." ArXiv (2023). [paper] -
Anything-3D: Qiuhong Shen, Xingyi Yang, Xinchao Wang.
"Anything-3D: Towards Single-view Anything Reconstruction in the Wild." ArXiv (2023). [paper] [code] -
Any-to-Any Transfer: Songhua Liu, Jingwen Ye, Xinchao Wang.
"Any-to-Any Style Transfer: Making Picasso and Da Vinci Collaborate." ArXiv (2023). [paper] [code] -
Sheng He, Rina Bao, Jingpeng Li, Jeffrey Stout, Atle Bjornerud, P. Ellen Grant, Yangming Ou.
"Computer-Vision Benchmark Segment-Anything Model (SAM) in Medical Images: Accuracy in 12 Datasets." ArXiv (2023). [paper] -
SAM-Adapter: Tianrun Chen, Lanyun Zhu, Chaotao Ding, Runlong Cao, Yan Wang, Zejian Li, Lingyun Sun, Papa Mao, Ying Zang.
"SAM Fails to Segment Anything? -- SAM-Adapter: Adapting SAM in Underperformed Scenes: Camouflage, Shadow, Medical Image Segmentation, and More." ArXiv (2023). [paper] -
Chuanfei Hu, Tianyi Xia, Shenghong Ju, Xinde Li.
" When SAM Meets Medical Images: An Investigation of Segment Anything Model (SAM) on Multi-phase Liver Tumor Segmentation." ArXiv (2023). [paper] -
SATIR: Junzhang Chen, Xiangzhi Bai.
" Learning to "Segment Anything" in Thermal Infrared Images through Knowledge Distillation with a Large Scale Dataset SATIR." ArXiv (2023). [paper] [code] -
Florian Putz, Johanna Grigo, Thomas Weissmann, Philipp Schubert, Daniel Hoefler, Ahmed Gomaa, Hassen Ben Tkhayat, Amr Hagag, Sebastian Lettmaier, Benjamin Frey, Udo S. Gaipl, Luitpold V. Distel, Sabine Semrau, Christoph Bert, Rainer Fietkau, Yixing Huang.
"The Segment Anything foundation model achieves favorable brain tumor autosegmentation accuracy on MRI to support radiotherapy treatment planning." ArXiv (2023). [paper] -
Iraklis Giannakis, Anshuman Bhardwaj, Lydia Sam, Georgios Leontidis.
" Deep learning universal crater detection using Segment Anything Model (SAM)." ArXiv (2023). [paper] -
SAMPolyp: Tao Zhou, Yizhe Zhang, Yi Zhou, Ye Wu, Chen Gong.
" Can SAM Segment Polyps?" ArXiv (2023). [paper] [code] -
Inpaint-Anything: Tao Yu, Runseng Feng, Ruoyu Feng, Jinming Liu, Xin Jin, Wenjun Zeng, Zhibo Chen.
"Inpaint Anything: Segment Anything Meets Image Inpainting." ArXiv (2023). [paper] [code] -
Ge-Peng Ji, Deng-Ping Fan, Peng Xu, Ming-Ming Cheng, Bowen Zhou, Luc Van Gool.
" SAM Struggles in Concealed Scenes -- Empirical Study on "Segment Anything"." ArXiv (2023). [paper] -
Wei Ji, Jingjing Li, Qi Bi, Wenbo Li, Li Cheng.
"Segment Anything Is Not Always Perfect: An Investigation of SAM on Different Real-world Applications." ArXiv (2023). [paper] -
CLIP Surgery: Yi Li, Hualiang Wang, Yiqun Duan, Xiaomeng Li.
"CLIP Surgery for Better Explainability with Enhancement in Open-Vocabulary Tasks." ArXiv (2023). [paper] [code] -
SAMM: Yihao Liu, Jiaming Zhang, Zhangcong She, Amir Kheradmand, Mehran Armand.
"SAMM (Segment Any Medical Model): A 3D Slicer Integration to SAM." ArXiv (2023). [paper] [code] -
SAM.MD: Saikat Roy, Tassilo Wald, Gregor Koehler, Maximilian R. Rokuss, Nico Disch, Julius Holzschuh, David Zimmerer, Klaus H. Maier-Hein.
"SAM.MD: Zero-shot medical image segmentation capabilities of the Segment Anything Model." ArXiv (2023). [paper] -
SAM vs BET: Sovesh Mohapatra, Advait Gosai, Gottfried Schlaug.
"SAM vs BET: A Comparative Study for Brain Extraction and Segmentation of Magnetic Resonance Images using Deep Learning." ArXiv (2023). [paper] [code] -
SAMCOD: Lv Tang, Haoke Xiao, Bo Li.
"Can SAM Segment Anything? When SAM Meets Camouflaged Object Detection." ArXiv (2023). [paper] [code]
| No. | Project | Title | Project page | Code base | Affiliation | Description |
|---|---|---|---|---|---|---|
| 001 | SAM | Segment Anything | Project page | Code | Meta | A foundation model for general segmentation. |
| 002 | SAM-Track | Segment and Track Anything | Colab | Code | Zhejiang University | A project dedicated to tracking and segmenting any objects in videos, either automatically or interactively. |
| 003 | Grounded-SAM | Grounded-Segment-Anything | Colab | Code | IDEA-Research | A project by combining Grounding DINO and SAM which aims to detect and segment Anything with text inputs. |
| 004 | MMDet-SAM | - | - | Code | OpenMMLab | A new way of instance segmentation by combining SAM with Closed-Set Object Detection, Open-Vocabulary Object Detection, Grounding Object Detection. |
| 005 | MMRotate-SAM | Zero-shot Oriented Object Detection with SAM | - | Code | OpenMMLab | A project join SAM and weakly supervised horizontal box detection to achieve rotated box detection. |
| 006 | MMOCR-SAM | - | - | Code | OpenMMLab | A solution of Text Detection/Recognition and SAM that segments every text character, with striking text removal and text inpainting demos driven by diffusion models and Gradio. |
| 007 | MMEditing-SAM | - | - | Code | OpenMMLab | A project join SAM and image generation to create awesome images and edit any part of them. |
| 008 | Label-Studio-SAM | OpenMMLab PlayGround: Semi-Automated Annotation with Label-Studio and SAM | - | Code | OpenMMLab | A project combining Label-Studio and SAM to achieve semi-automated annotation. |
| 009 | PaddleSeg | Segment Anything with PaddleSeg | - | Code | PaddlePaddle | A pretrained model parameters of PaddlePaddle format. |
| 010 | SegGPT | Segmenting Everything In Context | Hugging Face | Code | BAAI-Vision | SAM In Context based on Painter. |
| 011 | SEEM | Segment Everything Everywhere All at Once | Hugging Face | Code | Microsoft | A project can Segment Everything Everywhere with Multi-modal prompts all at once. |
| 012 | CLIP Surgery | CLIP Surgery for Better Explainability with Enhancement in Open Vocabulary Tasks | Project page | Code | HKUST | A work about SAM based on CLIP's explainability to achieve text to mask without manual points. |
| 013 | SAMCOD | Can SAM Segment Anything? When SAM Meets Camouflaged Object Detection | - | Code | - | SAM +Camouflaged object detection (COD) task. |
| 014 | Inpaint Anything | Segment Anything Meets Image Inpainting | Hugging Face | Code | USTC and EIT | SAM combines Inpainting, which is able to remove the object smoothly. |
| 015 | PerSAM | Personalize Segment Anything Model with One Shot | Hugging Face | Code | - | SAM with specific concepts. |
| 016 | MedSAM | Segment Anything in Medical Images | - | Code | - | A step-by-step tutorial with a small dataset to help you quickly utilize SAM. |
| 017 | Segment-Any-Anomaly | GroundedSAM Anomaly Detection | Colab | Code | HUST | Grounding DINO + SAM to segment any anomaly. |
| 018 | SSA | Semantic Segment Anything | - | Code | Fudan University | A dense category annotation engine. |
| 019 | Magic Copy | - | - | Code | - | Magic Copy is a Chrome extension that uses SAM to extract a foreground object from an image and copy it to the clipboard. |
| 020 | Segment Anything with Clip | Segment Anything with Clip | Hugging Face | Code | - | SAM combined with CLIP. |
| 021 | MetaSeg | Segment Anything Video | Hugging Face | Code | - | Packaged version of the SAM. |
| 022 | SAM in Napari | Segment Anything Model (SAM) in Napari | Project page | Code | Applied Computer Vision Lab and German Cancer Research Center | Extended SAM's click-based foreground separation to full click-based semantic segmentation and instance segmentation. |
| 023 | SAM Medical Imaging | SAM Medical Imaging | - | Code | - | SAM for Medical Imaging. |
| 024 | 3D-Box | 3D-Box via Segment Anything | - | Code | - | SAM is extended to 3D perception by combining it with VoxelNeXt. |
| 025 | Anything-3D | - | - | Code | - | Anything 3DNovel View, Anything-NeRF, Any 3DFace. |
| 026 | L2SET | Learning to Segment EveryThing | - | Code | UC Berkeley, FAIR | A new partially supervised training paradigm for instance segmentation. |
| 027 | Edit Anything | Edit Anything by Segment-Anything | - | Code | - | Edit anything in images powered by SAM, ControlNet, StableDiffusion, \etc. |
| 028 | Image Edit Anything | IEA: Image Editing Anything | - | Code | - | Using stable diffusion and SAM for image editing. |
| 029 | SAM for Stable Diffusion Webui | Segment Anything for Stable Diffusion WebUI | - | Code | - | This extension aim for connecting AUTOMATIC1111 Stable Diffusion WebUI and Mikubill ControlNet Extension with SAM and GroundingDINO to enhance Stable Diffusion/ControlNet inpainting. |
| 030 | Earth Observation Tools | Segment Anything EO tools | Colab | Code | - | An earth observation tools for SAM. |
| 031 | Moving Object Detection | Towards Segmenting Anything That Moves | - | Code | - | A project about SAM + Moving Object Detection. |
| 032 | OCR-SAM | Optical Character Recognition with Segment Anything | Project page | Code | - | Combining MMOCR with SAM and Stable Diffusion. |
| 033 | SALT | Segment Anything Labelling Tool | - | Code | - | A project uses the SAM Model and adds a barebones interface to label images and saves the masks in the COCO format. |
| 034 | Prompt Segment Anything | Prompt Segment Anything | - | Code | - | An implementation of zero-shot instance segmentation using SAM. |
| 035 | SAM-RBox | - | - | Code | - | A project uses SAM for generating rotated bounding boxes with MMRotate, which is a comparison method of H2RBox-v2. |
| 036 | VISAM | MOTRv2: Bootstrapping End-to-End Multi-Object Tracking by Pretrained Object Detectors | - | Code | - | Combining SAM with MOT, it create the era of "MOTS". |
| 037 | SegEO | Segment Anything EO tools | - | Code | - | The tools are developed to ease the processing of spatial data (GeoTIFF and TMS) with SAM using sliding window algorithm for big files. |
| 038 | Napari Segment Anything | Napari Segment Anything | Project page | Code | - | SAM native Qt UI. |
| 039 | Segment-Anything-U-Specify | Segment-Anything-U-Specify | - | Code | - | Using CLIP and SAM to segment any instance you specify with text prompt of any instance names. |
| 040 | SegDrawer | Simple static web-based mask drawer | Colab | Code | - | Simple static web-based mask drawer, supporting semantic segmentation with SAM. |
| 041 | Track Anything | Segment Anything Meets Videos | Hugging Face | Code | SUSTech | Track-Anything is a flexible and interactive tool for video object tracking and segmentation. |
| 042 | Count Anything | - | - | Code | - | A method uses SAM and CLIP to ground and count any object that matches a custom text prompt, without requiring any point or box annotation. |
| 043 | RAM | Relate Anything Model | Hugging Face | Code | MMLab, NTU and VisCom Lab, KCL/TongJi | Relate Anything Model is capable of taking an image as input and utilizing SAM to identify the corresponding mask within the image. |
| 044 | Segment Any RGBD | Segment Any RGBD | Project page | Code | - | Segment AnyRGBD is a toolbox to segment rendered depth images based on SAM. |
| 045 | Show Anything | Show Anything | Hugging Face | Code | Showlab, NUS | Some Applications that are compatible with both SAM and Generation. |
| 046 | Transfer Any Style | Any-to-Any Style Transfer: Making Picasso and Da Vinci Collaborate | - | Code | LV-lab, NUS | An interactive demo based on Segment-Anything for style transfer which enables different content regions apply different styles. |
| 047 | Caption Anything | - | Colab | Code | VIP lab, SUSTech | Caption-Anything is a versatile image processing tool that combines the capabilities of SAM, Visual Captioning, and ChatGPT. |
| 048 | Image2Paragraph | Transform Image Into Unique Paragraph | Project page | Code | - | Transform Image into Unique Paragraph with ChatGPT, BLIP2, OFA, GRIT, Segment Anything, ControlNet. |
| 049 | LIME SAM | Local Interpretable Model-agnostic Explanations Segment Anything | Colab | Code | - | LIME-SAM aims to create an Explainable Artificial Intelligence (XAI) framework for image classification using LIME (Local Interpretable Model-agnostic Explanations) as the base algorithm, with the super-pixel method replaced by SAM. |
| 050 | Paint Anything | - | - | Code | - | An interactive demo based on SAM for stroke-based painting which enables human-like painting. |
| 051 | SAMed | Customized Segment Anything Model for Medical Image Segmentation | Colab | Code | USTC | SAMed is built upon the large-scale image segmentation model, SAM, to explore the new research paradigm of customizing large-scale models for medical image segmentation. |
| 052 | Personalize SAM | Personalize Segment Anything with 1 Shot in 10 Seconds | Hugging Face | Code | MMLab, CUHK | A training-free Personalization approach for SAM, termed as PerSAM. Given only a single image with a reference mask, PerSAM can segment specific visual concepts. |
| 053 | Open-vocabulary-Segment-Anything | Open-vocabulary-Segment-Anything | - | Code | - | Combining OwlViT with Segment Anything - Open-vocabulary Detection and Segmentation (Text-conditioned, and Image-conditioned). |
| 054 | Labal-Anything-Pipeline | Label-Anything-Pipeline | - | Code | ZJU | Annotation anything in visual tasks just all in one-pipeline with GPT-4 and SAM. |
| 055 | Grounded-Segment-Any-Parts | Grounded Segment Anything: From Objects to Parts | Project page | Code | HKU | Expand Segment Anything Model (SAM) to support text prompt input. The text prompt could be object-level(eg, dog) and part-level(eg, dog head). |
| 056 | AnyLabeling | AnyLabeling | Youtube page | Code | - | Effortless AI-assisted data labeling with AI support from Segment Anything and YOLO. |
| 057 | SSA | Semantic-Segment-Anything | Project page | Code | - | Automated dense category annotation engine that serves as the initial semantic labeling for the Segment Anything dataset (SA-1B). |
| 058 | RefSAM | Label Data with Segment Anything in Roboflow | Project page | Code | - | Referring Image Segmentation Benchmarking with Segment Anything Model (SAM). |
| 059 | Roboflow Annotate | Launch: Label Data with Segment Anything in Roboflow | Project page | APP | Roboflow | SAM-assisted labeling for training computer vision models. |
| 060 | ImageBind SAM | - | - | Code | IDEA-Research | This is an experimental demo aims to combine ImageBind and SAM to generate mask with different modalities. |