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Object Detection with Deep Learning: A Review

arXiv 1807.05511 ↗First posted 15 Jul 2018cs.CVcited by 524

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Abstract (arXiv)

Due to object detection's close relationship with video analysis and image understanding, it has attracted much research attention in recent years. Traditional object detection methods are built on handcrafted features and shallow trainable architectures. Their performance easily stagnates by constructing complex ensembles which combine multiple low-level image features with high-level context from object detectors and scene classifiers. With the rapid development in deep learning, more powerful tools, which are able to learn semantic, high-level, deeper features, are introduced to address the problems existing in traditional architectures. These models behave differently in network architecture, training strategy and optimization function, etc. In this paper, we provide a review on deep learning based object detection frameworks. Our review begins with a brief introduction on the history of deep learning and its representative tool, namely Convolutional Neural Network (CNN). Then we focus on typical generic object detection architectures along with some modifications and useful tricks to improve detection performance further. As distinct specific detection tasks exhibit different characteristics, we also briefly survey several specific tasks, including salient object detection, face detection and pedestrian detection. Experimental analyses are also provided to compare various methods and draw some meaningful conclusions. Finally, several promising directions and tasks are provided to serve as guidelines for future work in both object detection and relevant neural network based learning systems.

Key facts. Cited by 524 papers in the map (data through 7 Oct 2026). First posted on arXiv 15 Jul 2018.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 123; 2022: 118; 2023: 101; 2024: 87; 2025: 59; 2026: 36.

524 papers.

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  1. 2024YOLOv11: An Overview of the Key Architectural Enhancementscited by 414
  2. 2021Concealed Object Detectioncited by 212
  3. 2022VLP: A Survey on Vision-Language Pre-trainingcited by 159
  4. 2022Towards Large-Scale Small Object Detection: Survey and Benchmarkscited by 119
  5. 2021A Survey of Visual Transformerscited by 117
  6. 2021Dive into Deep Learningcited by 111
  7. 2021Invisible for both Camera and LiDAR: Security of Multi-Sensor Fusion based Perception in Autonomous Driving Under Physical-World Attackscited by 101
  8. 2021A Survey of Modern Deep Learning based Object Detection Modelscited by 97
  9. 2021Unsupervised Domain Adaptation of Object Detectors: A Surveycited by 93
  10. 2021Image-Adaptive YOLO for Object Detection in Adverse Weather Conditionscited by 85
  11. 2022Temporal Action Segmentation: An Analysis of Modern Techniquescited by 85
  12. 2021Deep Learning for Chest X-ray Analysis: A Surveycited by 84
38 more
  1. 2025YOLO26: Key Architectural Enhancements and Performance Benchmarking for Real-Time Object Detectioncited by 76
  2. 2021Unbox the Black-box for the Medical Explainable AI via Multi-modal and Multi-centre Data Fusion: A Mini-Review, Two Showcases and Beyondcited by 75
  3. 2023A Comprehensive Survey on Applications of Transformers for Deep Learning Taskscited by 70
  4. 2022A Large-scale Multiple-objective Method for Black-box Attack against Object Detectioncited by 55
  5. 2021A Comprehensive Review of Computer-aided Whole-slide Image Analysis: from Datasets to Feature Extraction, Segmentation, Classification, and Detection Approachescited by 44
  6. 2022Phase-Shifting Coder: Predicting Accurate Orientation in Oriented Object Detectioncited by 43
  7. 2023Federated Learning for Connected and Automated Vehicles: A Survey of Existing Approaches and Challengescited by 39
  8. 2021VINS: Visual Search for Mobile User Interface Designcited by 37
  9. 2021The SARAS Endoscopic Surgeon Action Detection (ESAD) dataset: Challenges and methodscited by 37
  10. 2022Visual Attention Methods in Deep Learning: An In-Depth Surveycited by 37
  11. 2022Deep Learning-Enabled Semantic Communication Systems with Task-Unaware Transmitter and Dynamic Datacited by 36
  12. 2021PaddleSeg: A High-Efficient Development Toolkit for Image Segmentationcited by 33
  13. 2021A Review on Deep Learning in UAV Remote Sensingcited by 32
  14. 2023HiDAnet: RGB-D Salient Object Detection via Hierarchical Depth Awarenesscited by 31
  15. 2022Green Learning: Introduction, Examples and Outlookcited by 30
  16. 2021TS-MULE: Local Interpretable Model-Agnostic Explanations for Time Series Forecast Modelscited by 28
  17. 2021Few-Shot Object Detection: A Comprehensive Surveycited by 28
  18. 2022Untargeted Backdoor Attack against Object Detectioncited by 28
  19. 2023H2RBox-v2: Incorporating Symmetry for Boosting Horizontal Box Supervised Oriented Object Detectioncited by 28
  20. 2024VISA: Retrieval Augmented Generation with Visual Source Attributioncited by 28
  21. 2022Weakly Aligned Feature Fusion for Multimodal Object Detectioncited by 26
  22. 2024Safeguarding Vision-Language Models Against Patched Visual Prompt Injectorscited by 26
  23. 2021Occlusion Handling in Generic Object Detection: A Reviewcited by 25
  24. 2021Unmanned Aerial Vehicle Visual Detection and Tracking using Deep Neural Networks: A Performance Benchmarkcited by 25
  25. 2021Learning Visual Affordance Grounding from Demonstration Videoscited by 25
  26. 2022One-shot Neural Backdoor Erasing via Adversarial Weight Maskingcited by 25
  27. 2022EgoLoc: Revisiting 3D Object Localization from Egocentric Videos with Visual Queriescited by 25
  28. 2023Towards Transferable Targeted 3D Adversarial Attack in the Physical Worldcited by 25
  29. 2023LLMind: Orchestrating AI and IoT with LLM for Complex Task Executioncited by 24
  30. 2022Vision+X: A Survey on Multimodal Learning in the Light of Datacited by 22
  31. 2022The Enemy of My Enemy is My Friend: Exploring Inverse Adversaries for Improving Adversarial Trainingcited by 22
  32. 2023Confident Object Detection via Conformal Prediction and Conformal Risk Control: an Application to Railway Signalingcited by 22
  33. 2023A Survey on Reservoir Computing and its Interdisciplinary Applications Beyond Traditional Machine Learningcited by 22
  34. 2024ConjNorm: Tractable Density Estimation for Out-of-Distribution Detectioncited by 22
  35. 2023Point2RBox: Combine Knowledge from Synthetic Visual Patterns for End-to-end Oriented Object Detection with Single Point Supervisioncited by 21
  36. 2023Multimodality of AI for Education: Towards Artificial General Intelligencecited by 21
  37. 2023Deep Learning for Inertial Positioning: A Surveycited by 20
  38. 2021A Unified Benchmark for the Unknown Detection Capability of Deep Neural Networkscited by 19

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