# What is YOLOv8: An In-Depth Exploration of the Internal Features of the Next-Generation Object Detector

arXiv: https://arxiv.org/abs/2408.15857 · HTML: https://mlsanity.com/paper/2408.15857/

## Key facts

- Cited by 45 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 25 references that are in the map.
- First posted on arXiv 28 Aug 2024.

## Builds on (most cited first, 3 of 3)

- [You Only Look Once: Unified, Real-Time Object Detection](https://mlsanity.com/paper/1506.02640/) (2015)
- [YOLOv4: Optimal Speed and Accuracy of Object Detection](https://mlsanity.com/paper/2004.10934/) (2020)
- [What is YOLOv5: A deep look into the internal features of the popular object detector](https://mlsanity.com/paper/2407.20892/) (2024)

## Built on by (most cited first, 30 of 45)

- [ManipDreamer3D : Synthesizing Plausible Robotic Manipulation Video with Occupancy-aware 3D Trajectory](https://mlsanity.com/paper/2509.05314/) (2025)
- [What is YOLOv9: An In-Depth Exploration of the Internal Features of the Next-Generation Object Detector](https://mlsanity.com/paper/2409.07813/) (2024)
- [OV-DEIM: Real-time DETR-Style Open-Vocabulary Object Detection with GridSynthetic Augmentation](https://mlsanity.com/paper/2603.07022/) (2026)
- [Out of Sight, Still in Mind: Token Compression for Omni-LLMs](https://mlsanity.com/paper/2607.21179/) (2026)
- [An Analysis of Kalman Filter based Object Tracking Methods for Fast-Moving Tiny Objects](https://mlsanity.com/paper/2509.18451/) (2025)
- [A Comprehensive Evaluation of YOLO-based Deer Detection Performance on Edge Devices](https://mlsanity.com/paper/2509.20318/) (2025)
- [AI-Augmented Pollen Recognition in Optical and Holographic Microscopy for Veterinary Imaging](https://mlsanity.com/paper/2512.12101/) (2025)
- [Intelligent Traffic Surveillance for Real-Time Vehicle Detection, License Plate Recognition, and Speed Estimation](https://mlsanity.com/paper/2601.00344/) (2026)
- [UAV-DETR: DETR for Anti-Drone Target Detection](https://mlsanity.com/paper/2603.22841/) (2026)
- [Efficient Multi-Timescale Event Representations for Feed-Forward Object Detection](https://mlsanity.com/paper/2609.05049/) (2026)
- [Movie2Story: A framework for understanding videos and telling stories in the form of novel text](https://mlsanity.com/paper/2412.14965/) (2024)
- [EDocNet: Efficient Datasheet Layout Analysis Based on Focus and Global Knowledge Distillation](https://mlsanity.com/paper/2502.16541/) (2025)
- [Optimizing YOLOv8 for Parking Space Detection: Comparative Analysis of Custom YOLOv8 Architecture](https://mlsanity.com/paper/2505.17364/) (2025)
- [YOLO-APD: Enhancing YOLOv8 for Robust Pedestrian Detection on Complex Road Geometries](https://mlsanity.com/paper/2507.05376/) (2025)
- [YOLO-ROC: A High-Precision and Ultra-Lightweight Model for Real-Time Road Damage Detection](https://mlsanity.com/paper/2507.23225/) (2025)
- [YOLO-LAN: Precise Polyp Detection via Optimized Loss, Augmentations and Negatives](https://mlsanity.com/paper/2509.19166/) (2025)
- [Physics-Guided Fusion for Robust 3D Tracking of Fast Moving Small Objects](https://mlsanity.com/paper/2510.20126/) (2025)
- [VLSP 2025 MLQA-TSR Challenge: Vietnamese Multimodal Legal Question Answering on Traffic Sign Regulation](https://mlsanity.com/paper/2510.20381/) (2025)
- [hYOLO Model: Enhancing Object Classification with Hierarchical Context in YOLOv8](https://mlsanity.com/paper/2510.23278/) (2025)
- [Efficient License Plate Recognition via Pseudo-Labeled Supervision with Grounding DINO and YOLOv8](https://mlsanity.com/paper/2510.25032/) (2025)
- [Moving Pictures of Thought: Extracting Visual Knowledge in Charles S. Peirce's Manuscripts with Vision-Language Models](https://mlsanity.com/paper/2511.13378/) (2025)
- [MT-Depth: Multi-task Instance feature analysis for the Depth Completion](https://mlsanity.com/paper/2512.04734/) (2025)
- [Agent-Based Modular Learning for Multimodal Emotion Recognition in Human-Agent Systems](https://mlsanity.com/paper/2512.10975/) (2025)
- [Model-Centric Diagnostics: A Framework for Internal State Readouts](https://mlsanity.com/paper/2601.16874/) (2026)
- [A Scoping Review of Deep Learning for Urban Visual Pollution and Proposal of a Real-Time Monitoring Framework with a Visual Pollution Index](https://mlsanity.com/paper/2602.09446/) (2026)
- [SMR-Net:Robot Snap Detection Based on Multi-Scale Features and Self-Attention Network](https://mlsanity.com/paper/2603.01036/) (2026)
- [Tracking Feral Horses in Aerial Video Using Oriented Bounding Boxes](https://mlsanity.com/paper/2603.03604/) (2026)
- [MATHENA: Mamba-based Architectural Tooth Hierarchical Estimator and Holistic Evaluation Network for Anatomy](https://mlsanity.com/paper/2604.00537/) (2026)
- [SARES-DEIM: Sparse Mixture-of-Experts Meets DETR for Robust SAR Ship Detection](https://mlsanity.com/paper/2604.04127/) (2026)
- [DocRevive: A Unified Pipeline for Document Text Restoration](https://mlsanity.com/paper/2604.10077/) (2026)

## Abstract (arXiv)

This study presents a detailed analysis of the YOLOv8 object detection model, focusing on its architecture, training techniques, and performance improvements over previous iterations like YOLOv5. Key innovations, including the CSPNet backbone for enhanced feature extraction, the FPN+PAN neck for superior multi-scale object detection, and the transition to an anchor-free approach, are thoroughly examined. The paper reviews YOLOv8's performance across benchmarks like Microsoft COCO and Roboflow 100, highlighting its high accuracy and real-time capabilities across diverse hardware platforms. Additionally, the study explores YOLOv8's developer-friendly enhancements, such as its unified Python package and CLI, which streamline model training and deployment. Overall, this research positions YOLOv8 as a state-of-the-art solution in the evolving object detection field.