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Deep Learning for Generic Object Detection: A Survey

arXiv 1809.02165 ↗First posted 6 Sep 2018cs.CVcited by 392

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Abstract (arXiv)

Object detection, one of the most fundamental and challenging problems in computer vision, seeks to locate object instances from a large number of predefined categories in natural images. Deep learning techniques have emerged as a powerful strategy for learning feature representations directly from data and have led to remarkable breakthroughs in the field of generic object detection. Given this period of rapid evolution, the goal of this paper is to provide a comprehensive survey of the recent achievements in this field brought about by deep learning techniques. More than 300 research contributions are included in this survey, covering many aspects of generic object detection: detection frameworks, object feature representation, object proposal generation, context modeling, training strategies, and evaluation metrics. We finish the survey by identifying promising directions for future research.

Key facts. Cited by 392 papers in the map (data through 7 Oct 2026). First posted on arXiv 6 Sep 2018.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 106; 2022: 108; 2023: 86; 2024: 46; 2025: 31; 2026: 15.

392 papers.

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  1. 2021SwinIR: Image Restoration Using Swin Transformercited by 1,869
  2. 2022Activating More Pixels in Image Super-Resolution Transformercited by 433
  3. 2021AI and the Everything in the Whole Wide World Benchmarkcited by 340
  4. 2021Oriented R-CNN for Object Detectioncited by 230
  5. 2022VRT: A Video Restoration Transformercited by 219
  6. 2021Concealed Object Detectioncited by 212
  7. 2021Learning Distilled Collaboration Graph for Multi-Agent Perceptioncited by 194
  8. 2022Recurrent Video Restoration Transformer with Guided Deformable Attentioncited by 168
  9. 2021Pixel Difference Networks for Efficient Edge Detectioncited by 167
  10. 2023MixVPR: Feature Mixing for Visual Place Recognitioncited by 160
  11. 2021Camouflaged Object Segmentation with Distraction Miningcited by 151
  12. 2022Efficient Long-Range Attention Network for Image Super-resolutioncited by 151
38 more
  1. 2021NeSF: Neural Semantic Fields for Generalizable Semantic Segmentation of 3D Scenescited by 119
  2. 2022Towards Large-Scale Small Object Detection: Survey and Benchmarkscited by 119
  3. 2023Aligning Bag of Regions for Open-Vocabulary Object Detectioncited by 119
  4. 2021Recent advances and clinical applications of deep learning in medical image analysiscited by 104
  5. 2021Anchor-free Oriented Proposal Generator for Object Detectioncited by 104
  6. 2021A Survey of Modern Deep Learning based Object Detection Modelscited by 97
  7. 2021Region Similarity Representation Learningcited by 96
  8. 2022Image Data Augmentation for Deep Learning: A Surveycited by 96
  9. 2021Unsupervised Domain Adaptation of Object Detectors: A Surveycited by 93
  10. 2021ClevrTex: A Texture-Rich Benchmark for Unsupervised Multi-Object Segmentationcited by 93
  11. 2022GSV-Cities: Toward Appropriate Supervised Visual Place Recognitioncited by 92
  12. 2022Object Scene Representation Transformercited by 90
  13. 2021Class-agnostic Object Detection with Multi-modal Transformercited by 85
  14. 2021Deep Learning for Instance Retrieval: A Surveycited by 70
  15. 2023How Deep Learning Sees the World: A Survey on Adversarial Attacks & Defensescited by 65
  16. 2023HAT: Hybrid Attention Transformer for Image Restorationcited by 64
  17. 2021Unpaired Deep Image Deraining Using Dual Contrastive Learningcited by 60
  18. 2022Accelerating DETR Convergence via Semantic-Aligned Matchingcited by 58
  19. 2022CamoFormer: Masked Separable Attention for Camouflaged Object Detectioncited by 58
  20. 2021Semantics for Robotic Mapping, Perception and Interaction: A Surveycited by 56
  21. 2022A Survey on Graph Neural Networks and Graph Transformers in Computer Vision: A Task-Oriented Perspectivecited by 56
  22. 2023Strategic Preys Make Acute Predators: Enhancing Camouflaged Object Detectors by Generating Camouflaged Objectscited by 56
  23. 2022Instance Relation Graph Guided Source-Free Domain Adaptive Object Detectioncited by 55
  24. 2021Opening up Open-World Trackingcited by 50
  25. 2023Navigating to Objects Specified by Imagescited by 50
  26. 2022Meta-DETR: Image-Level Few-Shot Detection with Inter-Class Correlation Exploitationcited by 48
  27. 2021ViDT: An Efficient and Effective Fully Transformer-based Object Detectorcited by 45
  28. 2023Instance Segmentation in the Darkcited by 45
  29. 2021Meta-DETR: Image-Level Few-Shot Object Detection with Inter-Class Correlation Exploitationcited by 44
  30. 2021A comprehensive review of Binary Neural Networkcited by 44
  31. 2021Deep Learning for Micro-expression Recognition: A Surveycited by 43
  32. 2023MobileSAMv2: Faster Segment Anything to Everythingcited by 41
  33. 2022Feature Aggregation and Propagation Network for Camouflaged Object Detectioncited by 40
  34. 2021On Model Calibration for Long-Tailed Object Detection and Instance Segmentationcited by 39
  35. 2023SODFormer: Streaming Object Detection with Transformer Using Events and Framescited by 39
  36. 2021Decoupled Adaptation for Cross-Domain Object Detectioncited by 37
  37. 2022Multi-Objective Hyperparameter Optimization in Machine Learning -- An Overviewcited by 37
  38. 2022H2RBox: Horizontal Box Annotation is All You Need for Oriented Object Detectioncited by 36

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