mlsanityData to 7 Oct 2026

detrex: Benchmarking Detection Transformers

arXiv 2306.07265 ↗First posted 12 Jun 2023cs.CVcited by 8

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Abstract (arXiv)

The DEtection TRansformer (DETR) algorithm has received considerable attention in the research community and is gradually emerging as a mainstream approach for object detection and other perception tasks. However, the current field lacks a unified and comprehensive benchmark specifically tailored for DETR-based models. To address this issue, we develop a unified, highly modular, and lightweight codebase called detrex, which supports a majority of the mainstream DETR-based instance recognition algorithms, covering various fundamental tasks, including object detection, segmentation, and pose estimation. We conduct extensive experiments under detrex and perform a comprehensive benchmark for DETR-based models. Moreover, we enhance the performance of detection transformers through the refinement of training hyper-parameters, providing strong baselines for supported algorithms.We hope that detrex could offer research communities a standardized and unified platform to evaluate and compare different DETR-based models while fostering a deeper understanding and driving advancements in DETR-based instance recognition. Our code is available at https://github.com/IDEA-Research/detrex. The project is currently being actively developed. We encourage the community to use detrex codebase for further development and contributions.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 45 of its 54 references that are in the map. First posted on arXiv 12 Jun 2023.

Builds on

45 of 54 references.

References · 45

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2014Microsoft COCO: Common Objects in Contextcited by 17,498
  3. 2021Swin Transformer: Hierarchical Vision Transformer using Shifted Windowscited by 12,082
  4. 2015Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networkscited by 9,617
  5. 2020End-to-End Object Detection with Transformerscited by 7,384
  6. 2015You Only Look Once: Unified, Real-Time Object Detectioncited by 4,829
  7. 2016The Cityscapes Dataset for Semantic Urban Scene Understandingcited by 4,427
  8. 2022A ConvNet for the 2020scited by 3,545
  9. 2020Deformable DETR: Deformable Transformers for End-to-End Object Detectioncited by 3,410
  10. 2023Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detectioncited by 3,274
  11. 2015SSD: Single Shot MultiBox Detectorcited by 3,125
  12. 2021SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformerscited by 2,923
33 more
  1. 2021Masked-attention Mask Transformer for Universal Image Segmentationcited by 2,338
  2. 2020YOLOv4: Optimal Speed and Accuracy of Object Detectioncited by 1,624
  3. 2019FCOS: Fully Convolutional One-Stage Object Detectioncited by 1,573
  4. 2016YOLO9000: Better, Faster, Strongercited by 1,429
  5. 2019MMDetection: Open MMLab Detection Toolbox and Benchmarkcited by 1,379
  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. 2021Per-Pixel Classification is Not All You Need for Semantic Segmentationcited by 1,148
  9. 2021YOLOX: Exceeding YOLO Series in 2021cited by 1,064
  10. 2016Semantic Understanding of Scenes through the ADE20K Datasetcited by 1,063
  11. 2021MDETR -- Modulated Detection for End-to-End Multi-Modal Understandingcited by 811
  12. 2018CornerNet: Detecting Objects as Paired Keypointscited by 763
  13. 2022Exploring Plain Vision Transformer Backbones for Object Detectioncited by 723
  14. 2022DAB-DETR: Dynamic Anchor Boxes are Better Queries for DETRcited by 569
  15. 2023DETRs Beat YOLOs on Real-time Object Detectioncited by 526
  16. 2022DN-DETR: Accelerate DETR Training by Introducing Query DeNoisingcited by 486
  17. 2022InternImage: Exploring Large-Scale Vision Foundation Models with Deformable Convolutionscited by 479
  18. 2021Conditional DETR for Fast Training Convergencecited by 422
  19. 2022Mask DINO: Towards A Unified Transformer-based Framework for Object Detection and Segmentationcited by 341
  20. 2021Fast Convergence of DETR with Spatially Modulated Co-Attentioncited by 176
  21. 2022DETRs with Hybrid Matchingcited by 149
  22. 2023Dense Distinct Query for End-to-End Object Detectioncited by 76
  23. 2021ISTR: End-to-End Instance Segmentation with Transformerscited by 52
  24. 2023Explicit Box Detection Unifies End-to-End Multi-Person Pose Estimationcited by 48
  25. 2023Detection Transformer with Stable Matchingcited by 43
  26. 2023You Only Segment Once: Towards Real-Time Panoptic Segmentationcited by 40
  27. 2023MP-Former: Mask-Piloted Transformer for Image Segmentationcited by 39
  28. 2022NMS Strikes Backcited by 33
  29. 2022Group DETR v2: Strong Object Detector with Encoder-Decoder Pretrainingcited by 25
  30. 2022DQ-DETR: Dual Query Detection Transformer for Phrase Extraction and Groundingcited by 24
  31. 2021BoxeR: Box-Attention for 2D and 3D Transformerscited by 22
  32. 2023Boosting Human-Object Interaction Detection with Text-to-Image Diffusion Modelcited by 21
  33. 2023A Strong and Reproducible Object Detector with Only Public Datasetscited by 8

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 1; 2024: 2; 2025: 2; 2026: 3.

8 papers.

  1. 2024Grounded SAM: Assembling Open-World Models for Diverse Visual Taskscited by 914
  2. 2023Rank-DETR for High Quality Object Detectioncited by 49
  3. 2024LeanGaussian: Breaking Pixel or Point Cloud Correspondence in Modeling 3D Gaussianscited by 3
  4. 2025GeoPE:A Unified Geometric Positional Embedding for Structured Tensorscited by 2
  5. 2025Cross-DINO: Cross the Deep MLP and Transformer for Small Object Detectioncited by 1
  6. 2026Comparative Study of Out-of-the-Box Technology for Automatic Target Detection and Recognitioncited by 0
  7. 2026Enhanced Knowledge Distillation for Detection Transformer via Teacher Prediction Refinementcited by 0
  8. 2026Region-Aware CLS Token Augmentation for Fine-Grained Image Retrievalcited by 0