# Recent Advances in Deep Learning for Object Detection

arXiv: https://arxiv.org/abs/1908.03673 · HTML: https://mlsanity.com/paper/1908.03673/

## Key facts

- Cited by 50 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 10 Aug 2019.

## Built on by (most cited first, 30 of 50)

- [Contrastive Domain Adaptation](https://mlsanity.com/paper/2103.15566/) (2021)
- [A Review on Deep Learning in UAV Remote Sensing](https://mlsanity.com/paper/2101.10861/) (2021)
- [Perspectives on individual animal identification from biology and computer vision](https://mlsanity.com/paper/2103.00560/) (2021)
- [Continual Object Detection: A review of definitions, strategies, and challenges](https://mlsanity.com/paper/2205.15445/) (2022)
- [Spiking Neural Networks for Frame-based and Event-based Single Object Localization](https://mlsanity.com/paper/2206.06506/) (2022)
- [A Comprehensive Study of Real-Time Object Detection Networks Across Multiple Domains: A Survey](https://mlsanity.com/paper/2208.10895/) (2022)
- [On Board Volcanic Eruption Detection through CNNs and Satellite Multispectral Imagery](https://mlsanity.com/paper/2106.15281/) (2021)
- [Oriented object detection in optical remote sensing images using deep learning: a survey](https://mlsanity.com/paper/2302.10473/) (2023)
- [Automated Rip Current Detection with Region based Convolutional Neural Networks](https://mlsanity.com/paper/2102.02902/) (2021)
- [ABOShips -- An Inshore and Offshore Maritime Vessel Detection Dataset with Precise Annotations](https://mlsanity.com/paper/2102.05869/) (2021)
- [Few-shot Adaptive Object Detection with Cross-Domain CutMix](https://mlsanity.com/paper/2208.14586/) (2022)
- [TetraPackNet: Four-Corner-Based Object Detection in Logistics Use-Cases](https://mlsanity.com/paper/2104.09123/) (2021)
- [Detect Faces Efficiently: A Survey and Evaluations](https://mlsanity.com/paper/2112.01787/) (2021)
- [TreeFormer: a Semi-Supervised Transformer-based Framework for Tree Counting from a Single High Resolution Image](https://mlsanity.com/paper/2307.06118/) (2023)
- [SCD: A Stacked Carton Dataset for Detection and Segmentation](https://mlsanity.com/paper/2102.12808/) (2021)
- [TE-YOLOF: Tiny and efficient YOLOF for blood cell detection](https://mlsanity.com/paper/2108.12313/) (2021)
- [Weakly Supervised Lesion Detection and Diagnosis for Breast Cancers with Partially Annotated Ultrasound Images](https://mlsanity.com/paper/2306.06982/) (2023)
- [Improved Crop and Weed Detection with Diverse Data Ensemble Learning](https://mlsanity.com/paper/2310.01055/) (2023)
- [Semi-Supervised Object Detection: A Survey on Progress from CNN to Transformer](https://mlsanity.com/paper/2407.08460/) (2024)
- [YOLOv11 Optimization for Efficient Resource Utilization](https://mlsanity.com/paper/2412.14790/) (2024)
- [A Survey on Deep Domain Adaptation and Tiny Object Detection Challenges, Techniques and Datasets](https://mlsanity.com/paper/2107.07927/) (2021)
- [Deep Learning Innovations for Underwater Waste Detection: An In-Depth Analysis](https://mlsanity.com/paper/2405.18299/) (2024)
- [Holistic Approach to Measure Sample-level Adversarial Vulnerability and its Utility in Building Trustworthy Systems](https://mlsanity.com/paper/2205.02604/) (2022)
- [Team DETR: Guide Queries as a Professional Team in Detection Transformers](https://mlsanity.com/paper/2302.07116/) (2023)
- [EC-IoU: Orienting Safety for Object Detectors via Ego-Centric Intersection-over-Union](https://mlsanity.com/paper/2403.15474/) (2024)
- [Improved YOLOv5s model for key components detection of power transmission lines](https://mlsanity.com/paper/2502.06127/) (2025)
- [SimROD: A Simple Baseline for Raw Object Detection with Global and Local Enhancements](https://mlsanity.com/paper/2503.07101/) (2025)
- [Spatial-Temporal Map Vehicle Trajectory Detection Using Dynamic Mode Decomposition and Res-UNet+ Neural Networks](https://mlsanity.com/paper/2201.04755/) (2022)
- [Deep Learning Computer Vision Algorithms for Real-time UAVs On-board Camera Image Processing](https://mlsanity.com/paper/2211.01037/) (2022)
- [Accelerated Video Annotation driven by Deep Detector and Tracker](https://mlsanity.com/paper/2302.09590/) (2023)

## Abstract (arXiv)

Object detection is a fundamental visual recognition problem in computer vision and has been widely studied in the past decades. Visual object detection aims to find objects of certain target classes with precise localization in a given image and assign each object instance a corresponding class label. Due to the tremendous successes of deep learning based image classification, object detection techniques using deep learning have been actively studied in recent years. In this paper, we give a comprehensive survey of recent advances in visual object detection with deep learning. By reviewing a large body of recent related work in literature, we systematically analyze the existing object detection frameworks and organize the survey into three major parts: (i) detection components, (ii) learning strategies, and (iii) applications & benchmarks. In the survey, we cover a variety of factors affecting the detection performance in detail, such as detector architectures, feature learning, proposal generation, sampling strategies, etc. Finally, we discuss several future directions to facilitate and spur future research for visual object detection with deep learning. Keywords: Object Detection, Deep Learning, Deep Convolutional Neural Networks