mlsanityData to 7 Oct 2026

Segment Anything

arXiv 2304.02643 ↗First posted 5 Apr 2023cs.CV cs.AI cs.LGcited by 8,158

Not on the map. Why?

Cited by 696 in Multimodal LLMs / vision-language models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

We introduce the Segment Anything (SA) project: a new task, model, and dataset for image segmentation. Using our efficient model in a data collection loop, we built the largest segmentation dataset to date (by far), with over 1 billion masks on 11M licensed and privacy respecting images. The model is designed and trained to be promptable, so it can transfer zero-shot to new image distributions and tasks. We evaluate its capabilities on numerous tasks and find that its zero-shot performance is impressive -- often competitive with or even superior to prior fully supervised results. We are releasing the Segment Anything Model (SAM) and corresponding dataset (SA-1B) of 1B masks and 11M images at https://segment-anything.com to foster research into foundation models for computer vision.

Key facts. Cited by 8,158 papers in the map (data through 7 Oct 2026). Builds on 78 of its 149 references that are in the map. First posted on arXiv 5 Apr 2023.

Builds on

78 of 149 references.

References · 78

  1. 2017Attention Is All You Needcited by 59,932
  2. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  3. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  4. 2020Language Models are Few-Shot Learnerscited by 32,199
  5. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 29,915
  6. 2014Microsoft COCO: Common Objects in Contextcited by 17,498
  7. 2015Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networkscited by 9,617
  8. 2020End-to-End Object Detection with Transformerscited by 7,384
  9. 2021Masked Autoencoders Are Scalable Vision Learnerscited by 7,339
  10. 2017Mask R-CNNcited by 7,259
  11. 2020Scaling Laws for Neural Language Modelscited by 6,411
  12. 2016Layer Normalizationcited by 5,579
38 more
  1. 2022PaLM: Scaling Language Modeling with Pathwayscited by 5,304
  2. 2016The Cityscapes Dataset for Semantic Urban Scene Understandingcited by 4,427
  3. 2021Zero-Shot Text-to-Image Generationcited by 4,276
  4. 2021On the Opportunities and Risks of Foundation Modelscited by 3,961
  5. 2021Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervisioncited by 3,848
  6. 2016Gaussian Error Linear Units (GELUs)cited by 3,431
  7. 2022Training Compute-Optimal Large Language Modelscited by 2,927
  8. 2021BEiT: BERT Pre-Training of Image Transformerscited by 2,360
  9. 2021Masked-attention Mask Transformer for Universal Image Segmentationcited by 2,338
  10. 2016V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentationcited by 2,284
  11. 2020Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domainscited by 2,170
  12. 2013Rich feature hierarchies for accurate object detection and semantic segmentationcited by 2,160
  13. 2021Ego4D: Around the World in 3,000 Hours of Egocentric Videocited by 1,530
  14. 2017Accurate, Large Minibatch SGD: Training ImageNet in 1 Hourcited by 1,479
  15. 2018Datasheets for Datasetscited by 1,371
  16. 2017Cascade R-CNN: Delving into High Quality Object Detectioncited by 1,275
  17. 2019LVIS: A Dataset for Large Vocabulary Instance Segmentationcited by 1,215
  18. 2021Per-Pixel Classification is Not All You Need for Semantic Segmentationcited by 1,148
  19. 2018Model Cards for Model Reportingcited by 1,068
  20. 2016Semantic Understanding of Scenes through the ADE20K Datasetcited by 1,063
  21. 2016Deep Networks with Stochastic Depthcited by 973
  22. 2018Panoptic Segmentationcited by 796
  23. 2017Focal Loss for Dense Object Detectioncited by 749
  24. 2022Exploring Plain Vision Transformer Backbones for Object Detectioncited by 723
  25. 2020Simple Copy-Paste is a Strong Data Augmentation Method for Instance Segmentationcited by 595
  26. 2020Hypersim: A Photorealistic Synthetic Dataset for Holistic Indoor Scene Understandingcited by 593
  27. 2015Holistically-Nested Edge Detectioncited by 590
  28. 2021Carbon Emissions and Large Neural Network Trainingcited by 561
  29. 2020Rescaling Egocentric Visioncited by 529
  30. 2019Quantifying the Carbon Emissions of Machine Learningcited by 516
  31. 2017Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraintscited by 420
  32. 2022OneFormer: One Transformer to Rule Universal Image Segmentationcited by 327
  33. 2021K-Net: Towards Unified Image Segmentationcited by 211
  34. 2021Reviving Iterative Training with Mask Guidance for Interactive Segmentationcited by 162
  35. 2016Deep Interactive Object Selectioncited by 160
  36. 2019Towards Fairer Datasets: Filtering and Balancing the Distribution of the People Subtree in the ImageNet Hierarchycited by 156
  37. 2021Occluded Video Instance Segmentation: A Benchmarkcited by 154
  38. 2019Does Object Recognition Work for Everyone?cited by 149

50 most cited of 78 All 78 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 1091; 2024: 2478; 2025: 2749; 2026: 1840.

8,158 papers.

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  1. 2023Visual Instruction Tuningcited by 7,792
  2. 2023RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Controlcited by 2,993
  3. 2024SAM 2: Segment Anything in Images and Videoscited by 2,784
  4. 2025π0.5: a Vision-Language-Action Model with Open-World Generalizationcited by 1,653
  5. 2024Depth Anything V2cited by 1,385
  6. 2024Depth Anything: Unleashing the Power of Large-Scale Unlabeled Datacited by 1,346
  7. 2024Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Predictioncited by 1,005
  8. 2023ShareGPT4V: Improving Large Multi-Modal Models with Better Captionscited by 1,000
  9. 2023A Survey on Multimodal Large Language Modelscited by 898
  10. 2023Shikra: Unleashing Multimodal LLM's Referential Dialogue Magiccited by 891
  11. 2023PixArt-α: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesiscited by 854
  12. 2023Vision Transformers Need Registerscited by 844
38 more
  1. 2024Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMscited by 822
  2. 2023LISA: Reasoning Segmentation via Large Language Modelcited by 770
  3. 2023Objaverse-XL: A Universe of 10M+ 3D Objectscited by 767
  4. 2024Structured 3D Latents for Scalable and Versatile 3D Generationcited by 742
  5. 2024Show-o: One Single Transformer to Unify Multimodal Understanding and Generationcited by 734
  6. 2023VoxPoser: Composable 3D Value Maps for Robotic Manipulation with Language Modelscited by 733
  7. 2024DeepSeek-VL: Towards Real-World Vision-Language Understandingcited by 718
  8. 2023Animate Anyone: Consistent and Controllable Image-to-Video Synthesis for Character Animationcited by 683
  9. 2024SpatialVLM: Endowing Vision-Language Models with Spatial Reasoning Capabilitiescited by 679
  10. 2024RDT-1B: a Diffusion Foundation Model for Bimanual Manipulationcited by 670
  11. 2023Point Transformer V3: Simpler, Faster, Strongercited by 579
  12. 2024MathVerse: Does Your Multi-modal LLM Truly See the Diagrams in Visual Math Problems?cited by 573
  13. 2023One-2-3-45: Any Single Image to 3D Mesh in 45 Seconds without Per-Shape Optimizationcited by 555
  14. 2023Zero123++: a Single Image to Consistent Multi-view Diffusion Base Modelcited by 516
  15. 2025VideoLLaMA 3: Frontier Multimodal Foundation Models for Image and Video Understandingcited by 502
  16. 2025Visual-RFT: Visual Reinforcement Fine-Tuningcited by 501
  17. 2023Medical SAM Adapter: Adapting Segment Anything Model for Medical Image Segmentationcited by 485
  18. 2023End-to-end Autonomous Driving: Challenges and Frontierscited by 485
  19. 2024Evaluating Real-World Robot Manipulation Policies in Simulationcited by 484
  20. 2023Ego-Exo4D: Understanding Skilled Human Activity from First- and Third-Person Perspectivescited by 477
  21. 2023V*: Guided Visual Search as a Core Mechanism in Multimodal LLMscited by 459
  22. 2023GLaMM: Pixel Grounding Large Multimodal Modelcited by 447
  23. 2024Janus: Decoupling Visual Encoding for Unified Multimodal Understanding and Generationcited by 447
  24. 2023Generative Multimodal Models are In-Context Learnerscited by 446
  25. 2023AnyDoor: Zero-shot Object-level Image Customizationcited by 411
  26. 2023LangSplat: 3D Language Gaussian Splattingcited by 410
  27. 2023Florence-2: Advancing a Unified Representation for a Variety of Vision Taskscited by 403
  28. 2024Depth Pro: Sharp Monocular Metric Depth in Less Than a Secondcited by 395
  29. 2024OmniGen: Unified Image Generationcited by 388
  30. 2023Gaussian Grouping: Segment and Edit Anything in 3D Scenescited by 387
  31. 2024Hallucination of Multimodal Large Language Models: A Surveycited by 380
  32. 2025Reconstruction vs. Generation: Taming Optimization Dilemma in Latent Diffusion Modelscited by 376
  33. 2023Segment Anything in High Qualitycited by 373
  34. 2023Feature 3DGS: Supercharging 3D Gaussian Splatting to Enable Distilled Feature Fieldscited by 361
  35. 2024Mini-Gemini: Mining the Potential of Multi-modality Vision Language Modelscited by 361
  36. 2023DrivingGaussian: Composite Gaussian Splatting for Surrounding Dynamic Autonomous Driving Scenescited by 359
  37. 2023RemoteCLIP: A Vision Language Foundation Model for Remote Sensingcited by 357
  38. 2023ConceptGraphs: Open-Vocabulary 3D Scene Graphs for Perception and Planningcited by 357

50 most cited of 8,158 All 8,158 (JSON)