mlsanityData to 7 Oct 2026

Deformable DETR: Deformable Transformers for End-to-End Object Detection

arXiv 2010.04159 ↗First posted 8 Oct 2020cs.CVcited by 3,410

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Cited by 80 in Multimodal LLMs / vision-language models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

DETR has been recently proposed to eliminate the need for many hand-designed components in object detection while demonstrating good performance. However, it suffers from slow convergence and limited feature spatial resolution, due to the limitation of Transformer attention modules in processing image feature maps. To mitigate these issues, we proposed Deformable DETR, whose attention modules only attend to a small set of key sampling points around a reference. Deformable DETR can achieve better performance than DETR (especially on small objects) with 10 times less training epochs. Extensive experiments on the COCO benchmark demonstrate the effectiveness of our approach. Code is released at https://github.com/fundamentalvision/Deformable-DETR.

Key facts. Cited by 3,410 papers in the map (data through 7 Oct 2026). First posted on arXiv 8 Oct 2020.

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Citing papers per year: 2021: 306; 2022: 624; 2023: 779; 2024: 721; 2025: 589; 2026: 391.

3,410 papers.

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  1. 2021Swin Transformer: Hierarchical Vision Transformer using Shifted Windowscited by 12,082
  2. 2023Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detectioncited by 3,274
  3. 2021Masked-attention Mask Transformer for Universal Image Segmentationcited by 2,338
  4. 2021Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction without Convolutionscited by 1,960
  5. 2021Restormer: Efficient Transformer for High-Resolution Image Restorationcited by 1,618
  6. 2022DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detectioncited by 1,306
  7. 2022BEVFormer: Learning Bird's-Eye-View Representation from Multi-Camera Images via Spatiotemporal Transformerscited by 1,213
  8. 2021Grounded Language-Image Pre-trainingcited by 1,147
  9. 2021Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNetcited by 1,096
  10. 2022Planning-oriented Autonomous Drivingcited by 1,068
  11. 2021Transformers in Vision: A Surveycited by 1,009
  12. 2022YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectorscited by 978
38 more
  1. 2021UNETR: Transformers for 3D Medical Image Segmentationcited by 954
  2. 2021CvT: Introducing Convolutions to Vision Transformerscited by 946
  3. 2024Grounded SAM: Assembling Open-World Models for Diverse Visual Taskscited by 914
  4. 2021DynamicViT: Efficient Vision Transformers with Dynamic Token Sparsificationcited by 849
  5. 2022BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representationcited by 844
  6. 2023Vision-Language Models for Vision Tasks: A Surveycited by 834
  7. 2021ByteTrack: Multi-Object Tracking by Associating Every Detection Boxcited by 812
  8. 2021Domain Generalization: A Surveycited by 760
  9. 2022Exploring Plain Vision Transformer Backbones for Object Detectioncited by 723
  10. 2022AdaptFormer: Adapting Vision Transformers for Scalable Visual Recognitioncited by 714
  11. 2021DETR3D: 3D Object Detection from Multi-view Images via 3D-to-2D Queriescited by 655
  12. 2021Point-BERT: Pre-training 3D Point Cloud Transformers with Masked Point Modelingcited by 647
  13. 2021Transformer in Transformercited by 632
  14. 2022Detecting Twenty-thousand Classes using Image-level Supervisioncited by 613
  15. 2023VAD: Vectorized Scene Representation for Efficient Autonomous Drivingcited by 613
  16. 2022DAB-DETR: Dynamic Anchor Boxes are Better Queries for DETRcited by 569
  17. 2021Twins: Revisiting the Design of Spatial Attention in Vision Transformerscited by 565
  18. 2022Vision Transformer Adapter for Dense Predictionscited by 564
  19. 2022PETR: Position Embedding Transformation for Multi-View 3D Object Detectioncited by 550
  20. 2021TransMIL: Transformer based Correlated Multiple Instance Learning for Whole Slide Image Classificationcited by 549
  21. 2021CSWin Transformer: A General Vision Transformer Backbone with Cross-Shaped Windowscited by 526
  22. 2023DETRs Beat YOLOs on Real-time Object Detectioncited by 526
  23. 2021TrackFormer: Multi-Object Tracking with Transformerscited by 515
  24. 2024YOLOv10: Real-Time End-to-End Object Detectioncited by 508
  25. 2023VisionLLM: Large Language Model is also an Open-Ended Decoder for Vision-Centric Taskscited by 499
  26. 2024YOLO-World: Real-Time Open-Vocabulary Object Detectioncited by 498
  27. 2022DN-DETR: Accelerate DETR Training by Introducing Query DeNoisingcited by 486
  28. 2022InternImage: Exploring Large-Scale Vision Foundation Models with Deformable Convolutionscited by 479
  29. 2022TransFusion: Robust LiDAR-Camera Fusion for 3D Object Detection with Transformerscited by 464
  30. 2021Conditional DETR for Fast Training Convergencecited by 422
  31. 2023Tri-Perspective View for Vision-Based 3D Semantic Occupancy Predictioncited by 404
  32. 2023Florence-2: Advancing a Unified Representation for a Variety of Vision Taskscited by 403
  33. 2021Conditional Positional Encodings for Vision Transformerscited by 402
  34. 2021A Survey of Transformerscited by 399
  35. 2021MOTR: End-to-End Multiple-Object Tracking with Transformercited by 379
  36. 2021Rethinking Spatial Dimensions of Vision Transformerscited by 361
  37. 2022Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizationscited by 359
  38. 2022DiffusionDet: Diffusion Model for Object Detectioncited by 354

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