mlsanityData to 7 Oct 2026

Omni-DETR: Omni-Supervised Object Detection with Transformers

arXiv 2203.16089 ↗First posted 30 Mar 2022cs.CVcited by 28

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Abstract (arXiv)

We consider the problem of omni-supervised object detection, which can use unlabeled, fully labeled and weakly labeled annotations, such as image tags, counts, points, etc., for object detection. This is enabled by a unified architecture, Omni-DETR, based on the recent progress on student-teacher framework and end-to-end transformer based object detection. Under this unified architecture, different types of weak labels can be leveraged to generate accurate pseudo labels, by a bipartite matching based filtering mechanism, for the model to learn. In the experiments, Omni-DETR has achieved state-of-the-art results on multiple datasets and settings. And we have found that weak annotations can help to improve detection performance and a mixture of them can achieve a better trade-off between annotation cost and accuracy than the standard complete annotation. These findings could encourage larger object detection datasets with mixture annotations. The code is available at https://github.com/amazon-research/omni-detr.

Key facts. Cited by 28 papers in the map (data through 7 Oct 2026). Builds on 38 of its 53 references that are in the map. First posted on arXiv 30 Mar 2022.

Builds on

38 of 53 references.

References · 38

  1. 2017Attention Is All You Needcited by 59,932
  2. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  3. 2014Microsoft COCO: Common Objects in Contextcited by 17,498
  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. 2016Feature Pyramid Networks for Object Detectioncited by 5,021
  7. 2015You Only Look Once: Unified, Real-Time Object Detectioncited by 4,829
  8. 2020Deformable DETR: Deformable Transformers for End-to-End Object Detectioncited by 3,410
  9. 2015SSD: Single Shot MultiBox Detectorcited by 3,125
  10. 2015Fast R-CNNcited by 2,930
  11. 2013Rich feature hierarchies for accurate object detection and semantic segmentationcited by 2,160
  12. 2020FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidencecited by 2,080
26 more
  1. 2019FCOS: Fully Convolutional One-Stage Object Detectioncited by 1,573
  2. 2019Generalized Intersection over Union: A Metric and A Loss for Bounding Box Regressioncited by 1,361
  3. 2019Self-training with Noisy Student improves ImageNet classificationcited by 1,304
  4. 2017Cascade R-CNN: Delving into High Quality Object Detectioncited by 1,275
  5. 2019LVIS: A Dataset for Large Vocabulary Instance Segmentationcited by 1,215
  6. 2018Averaging Weights Leads to Wider Optima and Better Generalizationcited by 1,194
  7. 2021Unbiased Teacher for Semi-Supervised Object Detectioncited by 305
  8. 2015What's the Point: Semantic Segmentation with Point Supervisioncited by 297
  9. 2018CrowdHuman: A Benchmark for Detecting Human in a Crowdcited by 283
  10. 2020A Simple Semi-Supervised Learning Framework for Object Detectioncited by 282
  11. 2015Weakly Supervised Deep Detection Networkscited by 183
  12. 2021Humble Teachers Teach Better Students for Semi-Supervised Object Detectioncited by 115
  13. 2021Instant-Teaching: An End-to-End Semi-Supervised Object Detection Frameworkcited by 112
  14. 2018PCL: Proposal Cluster Learning for Weakly Supervised Object Detectioncited by 97
  15. 2018There Are Many Consistent Explanations of Unlabeled Data: Why You Should Averagecited by 82
  16. 2017Extreme clicking for efficient object annotationcited by 80
  17. 2021Exponential Moving Average Normalization for Self-supervised and Semi-supervised Learningcited by 78
  18. 2021Points as Queries: Weakly Semi-supervised Object Detection by Pointscited by 60
  19. 2021Rethinking Pseudo Labels for Semi-Supervised Object Detectioncited by 45
  20. 2018NOTE-RCNN: NOise Tolerant Ensemble RCNN for Semi-Supervised Object Detectioncited by 37
  21. 2017Deep Self-Taught Learning for Weakly Supervised Object Localizationcited by 27
  22. 2017Training object class detectors with click supervisioncited by 10
  23. 2019Active Learning with Point Supervision for Cost-Effective Panicle Detection in Cereal Cropscited by 8
  24. 2014Weakly-supervised Discovery of Visual Pattern Configurationscited by 7
  25. 2021WSSOD: A New Pipeline for Weakly- and Semi-Supervised Object Detectioncited by 7
  26. 2019Efficient Object Annotation via Speaking and Pointingcited by 6

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 5; 2023: 13; 2024: 6; 2025: 3; 2026: 1.

28 papers.

Sort:

  1. 2022GLIPv2: Unifying Localization and Vision-Language Understandingcited by 275
  2. 2022Learning Object-Language Alignments for Open-Vocabulary Object Detectioncited by 95
  3. 2022Semi-supervised Vision Transformers at Scalecited by 49
  4. 2023Semi-DETR: Semi-Supervised Object Detection with Detection Transformerscited by 27
  5. 2023Towards Unifying Anatomy Segmentation: Automated Generation of a Full-body CT Dataset via Knowledge Aggregation and Anatomical Guidelinescited by 17
  6. 2023Multiview Aerial Visual Recognition (MAVREC): Can Multi-view Improve Aerial Visual Perception?cited by 17
  7. 2024Sparse Semi-DETR: Sparse Learnable Queries for Semi-Supervised Object Detectioncited by 13
  8. 2024BSNet: Box-Supervised Simulation-assisted Mean Teacher for 3D Instance Segmentationcited by 9
  9. 2023ALWOD: Active Learning for Weakly-Supervised Object Detectioncited by 8
  10. 2023How to Efficiently Annotate Images for Best-Performing Deep Learning Based Segmentation Models: An Empirical Study with Weak and Noisy Annotations and Segment Anything Modelcited by 7
  11. 2023Semi-supervised Object Detection: A Survey on Recent Research and Progresscited by 5
  12. 2024What is Point Supervision Worth in Video Instance Segmentation?cited by 5
16 more
  1. 2022Adaptive Self-Training for Object Detectioncited by 4
  2. 2023Improving Human-Object Interaction Detection via Virtual Image Learningcited by 4
  3. 2024End-to-End Semi-Supervised approach with Modulated Object Queries for Table Detection in Documentscited by 4
  4. 2024Semi-Supervised Object Detection: A Survey on Progress from CNN to Transformercited by 4
  5. 2025BOOTPLACE: Bootstrapped Object Placement with Detection Transformerscited by 3
  6. 2025OmViD: Omni-supervised active learning for video action detectioncited by 3
  7. 2024Mixed-Query Transformer: A Unified Image Segmentation Architecturecited by 2
  8. 20221st Place Solutions for the UVO Challenge 2022cited by 1
  9. 2023Towards Universal Vision-language Omni-supervised Segmentationcited by 1
  10. 2023Deep Omni-supervised Learning for Rib Fracture Detection from Chest Radiology Imagescited by 1
  11. 2023Towards Omni-supervised Referring Expression Segmentationcited by 1
  12. 2023DeLR: Active Learning for Detection with Decoupled Localization and Recognition Querycited by 1
  13. 2025VFM-Guided Semi-Supervised Detection Transformer under Source-Free Constraints for Remote Sensing Object Detectioncited by 1
  14. 2023Rethinking Scale Imbalance in Semi-supervised Object Detection for Aerial Imagescited by 0
  15. 2023Seeking Flat Minima with Mean Teacher on Semi- and Weakly-Supervised Domain Generalization for Object Detectioncited by 0
  16. 2026Bridging Supervision Gaps: A Unified Framework for Remote Sensing Change Detectioncited by 0