mlsanityData to 14 Oct 2026

Siamese DETR

arXiv 2303.18144 ↗First posted 31 Mar 2023cs.CVcited by 8

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Abstract (arXiv)

Recent self-supervised methods are mainly designed for representation learning with the base model, e.g., ResNets or ViTs. They cannot be easily transferred to DETR, with task-specific Transformer modules. In this work, we present Siamese DETR, a Siamese self-supervised pretraining approach for the Transformer architecture in DETR. We consider learning view-invariant and detection-oriented representations simultaneously through two complementary tasks, i.e., localization and discrimination, in a novel multi-view learning framework. Two self-supervised pretext tasks are designed: (i) Multi-View Region Detection aims at learning to localize regions-of-interest between augmented views of the input, and (ii) Multi-View Semantic Discrimination attempts to improve object-level discrimination for each region. The proposed Siamese DETR achieves state-of-the-art transfer performance on COCO and PASCAL VOC detection using different DETR variants in all setups. Code is available at https://github.com/Zx55/SiameseDETR.

Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). Builds on 30 of its 41 references that are in the map. First posted on arXiv 31 Mar 2023.

Builds on

30 of 41 references.

References · 30

  1. 2017Attention Is All You Needcited by 60,361
  2. 2015Deep Residual Learning for Image Recognitioncited by 52,096
  3. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 30,186
  4. 2014Microsoft COCO: Common Objects in Contextcited by 17,608
  5. 2020A Simple Framework for Contrastive Learning of Visual Representationscited by 12,049
  6. 2019Momentum Contrast for Unsupervised Visual Representation Learningcited by 7,513
  7. 2020End-to-End Object Detection with Transformerscited by 7,414
  8. 2017Mask R-CNNcited by 7,277
  9. 2020Bootstrap your own latent: A new approach to self-supervised Learningcited by 4,750
  10. 2020Deformable DETR: Deformable Transformers for End-to-End Object Detectioncited by 3,422
  11. 2020Exploring Simple Siamese Representation Learningcited by 2,866
  12. 2020Unsupervised Learning of Visual Features by Contrasting Cluster Assignmentscited by 2,857
18 more
  1. 2020Improved Baselines with Momentum Contrastive Learningcited by 2,287
  2. 2019Generalized Intersection over Union: A Metric and A Loss for Bounding Box Regressioncited by 1,368
  3. 2022DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detectioncited by 1,319
  4. 2020Prototypical Contrastive Learning of Unsupervised Representationscited by 640
  5. 2022DAB-DETR: Dynamic Anchor Boxes are Better Queries for DETRcited by 573
  6. 2020Dense Contrastive Learning for Self-Supervised Visual Pre-Trainingcited by 512
  7. 2022DN-DETR: Accelerate DETR Training by Introducing Query DeNoisingcited by 488
  8. 2021Conditional DETR for Fast Training Convergencecited by 424
  9. 2021End-to-End Semi-Supervised Object Detection with Soft Teachercited by 316
  10. 2021Unbiased Teacher for Semi-Supervised Object Detectioncited by 306
  11. 2021DetCo: Unsupervised Contrastive Learning for Object Detectioncited by 205
  12. 2021Fast Convergence of DETR with Spatially Modulated Co-Attentioncited by 176
  13. 2021Efficient Visual Pretraining with Contrastive Detectioncited by 150
  14. 2021Aligning Pretraining for Detection via Object-Level Contrastive Learningcited by 110
  15. 2021DETReg: Unsupervised Pretraining with Region Priors for Object Detectioncited by 76
  16. 2021Unsupervised Object-Level Representation Learning from Scene Imagescited by 72
  17. 2018Re-Identification with Consistent Attentive Siamese Networkscited by 40
  18. 2021Self-Supervised Visual Representations Learning by Contrastive Mask Predictioncited by 31

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 2; 2024: 4; 2025: 0; 2026: 2.

8 papers.

  1. 2024RH20T-P: A Primitive-Level Robotic Dataset Towards Composable Generalization Agentscited by 20
  2. 2023T-MAE: Temporal Masked Autoencoders for Point Cloud Representation Learningcited by 11
  3. 2023Revisiting DETR Pre-training for Object Detectioncited by 5
  4. 2024Few-shot Online Anomaly Detection and Segmentationcited by 5
  5. 2024MutDet: Mutually Optimizing Pre-training for Remote Sensing Object Detectioncited by 5
  6. 2024Cross Resolution Encoding-Decoding For Detection Transformerscited by 0
  7. 2026What-Where Transformer: A Slot-Centric Visual Backbone for Concurrent Representation and Localizationcited by 0
  8. 2026Where to Look Matters: Rethinking Sub-Volume Sampling in 3D Medical Self-supervised Learningcited by 0