mlsanityData to 7 Oct 2026

Track Anything: Segment Anything Meets Videos

arXiv 2304.11968 ↗First posted 24 Apr 2023cs.CVcited by 230

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Abstract (arXiv)

Recently, the Segment Anything Model (SAM) gains lots of attention rapidly due to its impressive segmentation performance on images. Regarding its strong ability on image segmentation and high interactivity with different prompts, we found that it performs poorly on consistent segmentation in videos. Therefore, in this report, we propose Track Anything Model (TAM), which achieves high-performance interactive tracking and segmentation in videos. To be detailed, given a video sequence, only with very little human participation, i.e., several clicks, people can track anything they are interested in, and get satisfactory results in one-pass inference. Without additional training, such an interactive design performs impressively on video object tracking and segmentation. All resources are available on {https://github.com/gaomingqi/Track-Anything}. We hope this work can facilitate related research.

Key facts. Cited by 230 papers in the map (data through 7 Oct 2026). Builds on 9 of its 15 references that are in the map. First posted on arXiv 24 Apr 2023.

Builds on

9 of 15 references.

References · 9

  1. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 29,915
  2. 2023Segment Anythingcited by 8,158
  3. 2017The 2017 DAVIS Challenge on Video Object Segmentationcited by 942
  4. 2019Video Object Segmentation using Space-Time Memory Networkscited by 436
  5. 2022XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Modelcited by 436
  6. 2018Fast Online Object Tracking and Segmentation: A Unifying Approachcited by 272
  7. 2021Associating Objects with Transformers for Video Object Segmentationcited by 225
  8. 2021Modular Interactive Video Object Segmentation: Interaction-to-Mask, Propagation and Difference-Aware Fusioncited by 129
  9. 2022Towards An End-to-End Framework for Flow-Guided Video Inpaintingcited by 111

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 60; 2024: 87; 2025: 59; 2026: 24.

230 papers.

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  1. 2024SAM 2: Segment Anything in Images and Videoscited by 2,784
  2. 2023LangSplat: 3D Language Gaussian Splattingcited by 410
  3. 2023Faster Segment Anything: Towards Lightweight SAM for Mobile Applicationscited by 345
  4. 2023Personalize Segment Anything Model with One Shotcited by 250
  5. 2023Multimodal Foundation Models: From Specialists to General-Purpose Assistantscited by 247
  6. 2024Shape of Motion: 4D Reconstruction from a Single Videocited by 247
  7. 2023Tracking Anything with Decoupled Video Segmentationcited by 197
  8. 2023EfficientSAM: Leveraged Masked Image Pretraining for Efficient Segment Anythingcited by 187
  9. 2023Putting the Object Back into Video Object Segmentationcited by 182
  10. 2025FoundationStereo: Zero-Shot Stereo Matchingcited by 168
  11. 2023RoboAgent: Generalization and Efficiency in Robot Manipulation via Semantic Augmentations and Action Chunkingcited by 167
  12. 2024CAT4D: Create Anything in 4D with Multi-View Video Diffusion Modelscited by 160
38 more
  1. 2024Oryx MLLM: On-Demand Spatial-Temporal Understanding at Arbitrary Resolutioncited by 157
  2. 2023SAM-6D: Segment Anything Model Meets Zero-Shot 6D Object Pose Estimationcited by 115
  3. 2023Foundational Models Defining a New Era in Vision: A Survey and Outlookcited by 109
  4. 2023SurgicalSAM: Efficient Class Promptable Surgical Instrument Segmentationcited by 103
  5. 2024Dynamic Gaussian Marbles for Novel View Synthesis of Casual Monocular Videoscited by 96
  6. 2024TACO: Benchmarking Generalizable Bimanual Tool-ACtion-Object Understandingcited by 85
  7. 2023Segment Anything Meets Point Trackingcited by 81
  8. 2023Review of Large Vision Models and Visual Prompt Engineeringcited by 77
  9. 2024VRP-SAM: SAM with Visual Reference Promptcited by 75
  10. 2023Tool Documentation Enables Zero-Shot Tool-Usage with Large Language Modelscited by 66
  11. 2023A Comprehensive Survey on Segment Anything Model for Vision and Beyondcited by 64
  12. 2024Real-World Robot Applications of Foundation Models: A Reviewcited by 60
  13. 2024Theia: Distilling Diverse Vision Foundation Models for Robot Learningcited by 56
  14. 2024A Survey on Robotics with Foundation Models: toward Embodied AIcited by 53
  15. 2024Matching Anything by Segmenting Anythingcited by 49
  16. 2024Surgical SAM 2: Real-time Segment Anything in Surgical Video by Efficient Frame Pruningcited by 46
  17. 2023A Survey on Segment Anything Model (SAM): Vision Foundation Model Meets Prompt Engineeringcited by 45
  18. 2024REACTO: Reconstructing Articulated Objects from a Single Videocited by 45
  19. 2024Diffusion Model-Based Video Editing: A Surveycited by 44
  20. 2024SplineGS: Robust Motion-Adaptive Spline for Real-Time Dynamic 3D Gaussians from Monocular Videocited by 44
  21. 2023MobileSAMv2: Faster Segment Anything to Everythingcited by 41
  22. 2023DragVideo: Interactive Drag-style Video Editingcited by 40
  23. 2024Gaga: Group Any Gaussians via 3D-aware Memory Bankcited by 40
  24. 2023Matte Anything: Interactive Natural Image Matting with Segment Anything Modelscited by 39
  25. 2024RobustSAM: Segment Anything Robustly on Degraded Imagescited by 36
  26. 2024PTQ4SAM: Post-Training Quantization for Segment Anythingcited by 32
  27. 2024DarkSAM: Fooling Segment Anything Model to Segment Nothingcited by 32
  28. 2023Robustness of SAM: Segment Anything Under Corruptions and Beyondcited by 30
  29. 2024Hi-SAM: Marrying Segment Anything Model for Hierarchical Text Segmentationcited by 30
  30. 2023Unifying Image Processing as Visual Prompting Question Answeringcited by 29
  31. 2023Universal Segmentation at Arbitrary Granularity with Language Instructioncited by 29
  32. 2024UV-SAM: Adapting Segment Anything Model for Urban Village Identificationcited by 29
  33. 2024GoodSAM: Bridging Domain and Capacity Gaps via Segment Anything Model for Distortion-aware Panoramic Semantic Segmentationcited by 27
  34. 2023OpenVIS: Open-vocabulary Video Instance Segmentationcited by 25
  35. 2024UnrealZoo: Enriching Photo-realistic Virtual Worlds for Embodied AIcited by 25
  36. 2023RefSAM: Efficiently Adapting Segmenting Anything Model for Referring Video Object Segmentationcited by 24
  37. 2024Forging Vision Foundation Models for Autonomous Driving: Challenges, Methodologies, and Opportunitiescited by 24
  38. 2025Generative Physical AI in Vision: A Surveycited by 24

50 most cited of 230 All 230 (JSON)