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A Survey of Modern Deep Learning based Object Detection Models

arXiv 2104.11892 ↗First posted 24 Apr 2021cs.CV cs.LG eess.IVcited by 97

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Abstract (arXiv)

Object Detection is the task of classification and localization of objects in an image or video. It has gained prominence in recent years due to its widespread applications. This article surveys recent developments in deep learning based object detectors. Concise overview of benchmark datasets and evaluation metrics used in detection is also provided along with some of the prominent backbone architectures used in recognition tasks. It also covers contemporary lightweight classification models used on edge devices. Lastly, we compare the performances of these architectures on multiple metrics.

Key facts. Cited by 97 papers in the map (data through 7 Oct 2026). Builds on 77 of its 114 references that are in the map. First posted on arXiv 24 Apr 2021.

Builds on

77 of 114 references.

References · 77

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50 most cited of 77 All 77 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 5; 2022: 15; 2023: 40; 2024: 16; 2025: 18; 2026: 3.

97 papers.

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  1. 2023Guiding Pretraining in Reinforcement Learning with Large Language Modelscited by 185
  2. 2023Large Selective Kernel Network for Remote Sensing Object Detectioncited by 98
  3. 2024LSKNet: A Foundation Lightweight Backbone for Remote Sensingcited by 44
  4. 2021A Survey of Self-Supervised and Few-Shot Object Detectioncited by 35
  5. 2023A Survey on Deep Learning-Based Monocular Spacecraft Pose Estimation: Current State, Limitations and Prospectscited by 30
  6. 2023Object Detection with Transformers: A Reviewcited by 22
  7. 2023Inertial Navigation Meets Deep Learning: A Survey of Current Trends and Future Directionscited by 20
  8. 2022Towards Domain Generalization in Object Detectioncited by 16
  9. 2022Backbones-Review: Feature Extraction Networks for Deep Learning and Deep Reinforcement Learning Approachescited by 15
  10. 2023LARD -- Landing Approach Runway Detection -- Dataset for Vision Based Landingcited by 14
  11. 2025Strip R-CNN: Large Strip Convolution for Remote Sensing Object Detectioncited by 14
  12. 2023Less is More: Data Pruning for Faster Adversarial Trainingcited by 13
38 more
  1. 2023Divert More Attention to Vision-Language Object Trackingcited by 11
  2. 2023ObjectLab: Automated Diagnosis of Mislabeled Images in Object Detection Datacited by 11
  3. 2021A Comparative Review of Recent Few-Shot Object Detection Algorithmscited by 10
  4. 2022RF-Next: Efficient Receptive Field Search for Convolutional Neural Networkscited by 10
  5. 2022Multimodal Data Augmentation for Visual-Infrared Person ReID with Corrupted Datacited by 9
  6. 2022Archangel: A Hybrid UAV-based Human Detection Benchmark with Position and Pose Metadatacited by 8
  7. 2022Precise Single-stage Detectorcited by 7
  8. 2023Z-GMOT: Zero-shot Generic Multiple Object Trackingcited by 7
  9. 2023MFABA: A More Faithful and Accelerated Boundary-based Attribution Method for Deep Neural Networkscited by 7
  10. 2023Model-agnostic explainable artificial intelligence for object detection in image datacited by 6
  11. 2023Deep Learning Approaches for Seizure Video Analysis: A Reviewcited by 6
  12. 2024Domain Generalization with Small Datacited by 6
  13. 2024Run-time Introspection of 2D Object Detection in Automated Driving Systems Using Learning Representationscited by 6
  14. 2025Domain Randomization for Object Detection in Manufacturing Applications using Synthetic Data: A Comprehensive Studycited by 6
  15. 2025Neural Network Quantization for Microcontrollers: A Comprehensive Survey of Methods, Platforms, and Applicationscited by 6
  16. 2023Persistent Homology Meets Object Unity: Object Recognition in Cluttercited by 5
  17. 2023Semi-supervised Object Detection: A Survey on Recent Research and Progresscited by 5
  18. 2023A Review of Adversarial Attacks in Computer Visioncited by 5
  19. 2023Exploring the Performance and Efficiency of Transformer Models for NLP on Mobile Devicescited by 4
  20. 2023CREPE: Learnable Prompting With CLIP Improves Visual Relationship Predictioncited by 4
  21. 2023A tailored Handwritten-Text-Recognition System for Medieval Latincited by 4
  22. 2024DynaSeg: A Deep Dynamic Fusion Method for Unsupervised Image Segmentation Incorporating Feature Similarity and Spatial Continuitycited by 4
  23. 2024Latent Distillation for Continual Object Detection at the Edgecited by 4
  24. 2023Local and Global Contextual Features Fusion for Pedestrian Intention Predictioncited by 3
  25. 2023Real-Time Onboard Object Detection for Augmented Reality: Enhancing Head-Mounted Display with YOLOv8cited by 3
  26. 2024A Literature Review of Literature Reviews in Pattern Analysis and Machine Intelligencecited by 3
  27. 2024How Important are Data Augmentations to Close the Domain Gap for Object Detection in Orbit?cited by 3
  28. 2025A Decade of You Only Look Once (YOLO) for Object Detection: A Reviewcited by 3
  29. 2022Comparison of Object Detection Algorithms for Street-level Objectscited by 2
  30. 2023YOLO-based Object Detection in Industry 4.0 Fischertechnik Model Environmentcited by 2
  31. 2023Pallet Detection from Synthetic Data Using Game Enginescited by 2
  32. 2023Transferability Metrics for Object Detectioncited by 2
  33. 2023Propagating Semantic Labels in Video Datacited by 2
  34. 2024A Safety-Adapted Loss for Pedestrian Detection in Automated Drivingcited by 2
  35. 2024Improving Pallet Detection Using Synthetic Datacited by 2
  36. 2024Steal Now and Attack Later: Evaluating Robustness of Object Detection against Black-box Adversarial Attackscited by 2
  37. 2024FedPylot: Navigating Federated Learning for Real-Time Object Detection in Internet of Vehiclescited by 2
  38. 2025Few-Shot Learning in Video and 3D Object Detection: A Surveycited by 2

50 most cited of 97 All 97 (JSON)