mlsanityData to 14 Oct 2026

Meta-ZSDETR: Zero-shot DETR with Meta-learning

arXiv 2308.09540 ↗First posted 18 Aug 2023cs.CV cs.AIcited by 2

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Abstract (arXiv)

Zero-shot object detection aims to localize and recognize objects of unseen classes. Most of existing works face two problems: the low recall of RPN in unseen classes and the confusion of unseen classes with background. In this paper, we present the first method that combines DETR and meta-learning to perform zero-shot object detection, named Meta-ZSDETR, where model training is formalized as an individual episode based meta-learning task. Different from Faster R-CNN based methods that firstly generate class-agnostic proposals, and then classify them with visual-semantic alignment module, Meta-ZSDETR directly predict class-specific boxes with class-specific queries and further filter them with the predicted accuracy from classification head. The model is optimized with meta-contrastive learning, which contains a regression head to generate the coordinates of class-specific boxes, a classification head to predict the accuracy of generated boxes, and a contrastive head that utilizes the proposed contrastive-reconstruction loss to further separate different classes in visual space. We conduct extensive experiments on two benchmark datasets MS COCO and PASCAL VOC. Experimental results show that our method outperforms the existing ZSD methods by a large margin.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 33 of its 49 references that are in the map. First posted on arXiv 18 Aug 2023.

Builds on

33 of 49 references.

References · 33

  1. 2015Deep Residual Learning for Image Recognitioncited by 52,096
  2. 2014Microsoft COCO: Common Objects in Contextcited by 17,608
  3. 2015Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networkscited by 9,639
  4. 2018Representation Learning with Contrastive Predictive Codingcited by 7,777
  5. 2019Momentum Contrast for Unsupervised Visual Representation Learningcited by 7,513
  6. 2020End-to-End Object Detection with Transformerscited by 7,414
  7. 2015You Only Look Once: Unified, Real-Time Object Detectioncited by 4,852
  8. 2020Deformable DETR: Deformable Transformers for End-to-End Object Detectioncited by 3,422
  9. 2015Fast R-CNNcited by 2,933
  10. 2019Generalized Intersection over Union: A Metric and A Loss for Bounding Box Regressioncited by 1,368
  11. 2017Learning to Compare: Relation Network for Few-Shot Learningcited by 1,143
  12. 2017Feature Generating Networks for Zero-Shot Learningcited by 257
21 more
  1. 2017Advances in Pre-Training Distributed Word Representationscited by 207
  2. 2018Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoderscited by 206
  3. 2018Zero-Shot Object Detectioncited by 189
  4. 2019f-VAEGAN-D2: A Feature Generating Framework for Any-Shot Learningcited by 164
  5. 2017Semantic Autoencoder for Zero-Shot Learningcited by 133
  6. 2021Learning Open-World Object Proposals without Learning to Classifycited by 109
  7. 2021FREE: Feature Refinement for Generalized Zero-Shot Learningcited by 67
  8. 2019Dont Even Look Once: Synthesizing Features for Zero-Shot Detectioncited by 58
  9. 2018Zero-Shot Object Detection: Learning to Simultaneously Recognize and Localize Novel Conceptscited by 48
  10. 2021Zero-Shot Instance Segmentationcited by 40
  11. 2020Learning the Redundancy-free Features for Generalized Zero-Shot Object Recognitioncited by 34
  12. 2018Zero-Shot Object Detection by Hybrid Region Embeddingcited by 32
  13. 2020Synthesizing the Unseen for Zero-shot Object Detectioncited by 32
  14. 2020Background Learnable Cascade for Zero-Shot Object Detectioncited by 31
  15. 2021Semantics-Guided Contrastive Network for Zero-Shot Object detectioncited by 26
  16. 2020GTNet: Generative Transfer Network for Zero-Shot Object Detectioncited by 25
  17. 2016Improving Semantic Embedding Consistency by Metric Learning for Zero-Shot Classificationcited by 22
  18. 2022Robust Region Feature Synthesizer for Zero-Shot Object Detectioncited by 20
  19. 2022Recent Few-Shot Object Detection Algorithms: A Survey with Performance Comparisoncited by 8
  20. 2022Hierarchical Few-Shot Object Detection: Problem, Benchmark and Methodcited by 8
  21. 2023Frustratingly Simple but Effective Zero-shot Detection and Segmentation: Analysis and a Strong Baselinecited by 5

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 1.

2 papers.

  1. 2025Fine-Grained Zero-Shot Object Detectioncited by 8
  2. 2026SwiftGS: Episodic Priors for Immediate Satellite Surface Recoverycited by 0