mlsanityData to 7 Oct 2026

LVIS: A Dataset for Large Vocabulary Instance Segmentation

arXiv 1908.03195 ↗First posted 8 Aug 2019cs.CVcited by 1,215

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Cited by 141 in Multimodal LLMs / vision-language models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Progress on object detection is enabled by datasets that focus the research community's attention on open challenges. This process led us from simple images to complex scenes and from bounding boxes to segmentation masks. In this work, we introduce LVIS (pronounced `el-vis'): a new dataset for Large Vocabulary Instance Segmentation. We plan to collect ~2 million high-quality instance segmentation masks for over 1000 entry-level object categories in 164k images. Due to the Zipfian distribution of categories in natural images, LVIS naturally has a long tail of categories with few training samples. Given that state-of-the-art deep learning methods for object detection perform poorly in the low-sample regime, we believe that our dataset poses an important and exciting new scientific challenge. LVIS is available at http://www.lvisdataset.org.

Key facts. Cited by 1,215 papers in the map (data through 7 Oct 2026). First posted on arXiv 8 Aug 2019.

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Citing papers per year: 2021: 123; 2022: 172; 2023: 286; 2024: 259; 2025: 204; 2026: 171.

1,215 papers.

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  1. 2023Segment Anythingcited by 8,158
  2. 2023Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detectioncited by 3,274
  3. 2024SAM 2: Segment Anything in Images and Videoscited by 2,784
  4. 2022Objaverse: A Universe of Annotated 3D Objectscited by 1,522
  5. 2021Grounded Language-Image Pre-trainingcited by 1,147
  6. 2021Open-vocabulary Object Detection via Vision and Language Knowledge Distillationcited by 903
  7. 2023Shikra: Unleashing Multimodal LLM's Referential Dialogue Magiccited by 891
  8. 2023Vision-Language Models for Vision Tasks: A Surveycited by 834
  9. 2021MDETR -- Modulated Detection for End-to-End Multi-Modal Understandingcited by 811
  10. 2021Florence: A New Foundation Model for Computer Visioncited by 802
  11. 2023GLIGEN: Open-Set Grounded Text-to-Image Generationcited by 774
  12. 2022Exploring Plain Vision Transformer Backbones for Object Detectioncited by 723
38 more
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  2. 2022Detecting Twenty-thousand Classes using Image-level Supervisioncited by 613
  3. 2021RegionCLIP: Region-based Language-Image Pretrainingcited by 612
  4. 2024BLINK: Multimodal Large Language Models Can See but Not Perceivecited by 529
  5. 2021Image Segmentation Using Text and Image Promptscited by 509
  6. 2025Visual-RFT: Visual Reinforcement Fine-Tuningcited by 501
  7. 2023VisionLLM: Large Language Model is also an Open-Ended Decoder for Vision-Centric Taskscited by 499
  8. 2023Ferret: Refer and Ground Anything Anywhere at Any Granularitycited by 498
  9. 2024YOLO-World: Real-Time Open-Vocabulary Object Detectioncited by 498
  10. 2023End-to-end Autonomous Driving: Challenges and Frontierscited by 485
  11. 2022InternImage: Exploring Large-Scale Vision Foundation Models with Deformable Convolutionscited by 479
  12. 2023GLaMM: Pixel Grounding Large Multimodal Modelcited by 447
  13. 2022Unified-IO: A Unified Model for Vision, Language, and Multi-Modal Taskscited by 420
  14. 2021Deep Long-Tailed Learning: A Surveycited by 416
  15. 2023AnyDoor: Zero-shot Object-level Image Customizationcited by 411
  16. 2023FoundationPose: Unified 6D Pose Estimation and Tracking of Novel Objectscited by 411
  17. 2023EVA-02: A Visual Representation for Neon Genesiscited by 377
  18. 2023Segment Anything in High Qualitycited by 373
  19. 2023Open-Vocabulary Panoptic Segmentation with Text-to-Image Diffusion Modelscited by 371
  20. 2021ABO: Dataset and Benchmarks for Real-World 3D Object Understandingcited by 360
  21. 2022DiffusionDet: Diffusion Model for Object Detectioncited by 354
  22. 2024Prismatic VLMs: Investigating the Design Space of Visually-Conditioned Language Modelscited by 336
  23. 2023Scaling Open-Vocabulary Object Detectioncited by 335
  24. 2023PointLLM: Empowering Large Language Models to Understand Point Cloudscited by 326
  25. 2023OmniObject3D: Large-Vocabulary 3D Object Dataset for Realistic Perception, Reconstruction and Generationcited by 324
  26. 2022Learning to Prompt for Open-Vocabulary Object Detection with Vision-Language Modelcited by 317
  27. 2025Perception Encoder: The best visual embeddings are not at the output of the networkcited by 315
  28. 2022Simple Open-Vocabulary Object Detection with Vision Transformerscited by 303
  29. 2023Unified-IO 2: Scaling Autoregressive Multimodal Models with Vision, Language, Audio, and Actioncited by 301
  30. 2024SpatialRGPT: Grounded Spatial Reasoning in Vision Language Modelscited by 297
  31. 2023Fast Segment Anythingcited by 286
  32. 2023SPHINX: The Joint Mixing of Weights, Tasks, and Visual Embeddings for Multi-modal Large Language Modelscited by 283
  33. 2022GLIPv2: Unifying Localization and Vision-Language Understandingcited by 275
  34. 2022DETRs with Collaborative Hybrid Assignments Trainingcited by 273
  35. 2023PaLI-X: On Scaling up a Multilingual Vision and Language Modelcited by 254
  36. 2023Personalize Segment Anything Model with One Shotcited by 250
  37. 2022Language-Grounded Indoor 3D Semantic Segmentation in the Wildcited by 243
  38. 2024RoboPoint: A Vision-Language Model for Spatial Affordance Prediction for Roboticscited by 242

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