MHAF-YOLO: Multi-Branch Heterogeneous Auxiliary Fusion YOLO for accurate object detection
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Summary
This paper proposes MHAF-YOLO, a novel detection framework featuring a versatile neck design called the Multi-Branch Auxiliary FPN (MAFPN), which consists of two key modules: the Superficial Ass Fusion (SAF) and Advanced Ass Fusion (AAF).
- Type
- preprint
- Published
- 2025-02-07
- Cited by
- 37
- References
- 50
- Access
- Open access
- OpenAlex
- https://openalex.org/W4407309374
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:276236000
Keywords
Fusion, Artificial intelligence, Computer vision, Computer science, Object (grammar)
References
- Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
- You Only Look Once: Unified, Real-Time Object Detection
- The Pascal Visual Object Classes Challenge: A Retrospective
- ImageNet: A large-scale hierarchical image database
- Feature Pyramid Networks for Object Detection
- YOLO9000: Better, Faster, Stronger
- YOLOv3: An Incremental Improvement
- Hybrid Task Cascade for Instance Segmentation
- DOTA: A Large-Scale Dataset for Object Detection in Aerial Images
- Scale-Aware Trident Networks for Object Detection
- PANet: Few-Shot Image Semantic Segmentation With Prototype Alignment
- CSPNet: A New Backbone that can Enhance Learning Capability of CNN
- YOLOv4: Optimal Speed and Accuracy of Object Detection
- EfficientDet: Scalable and Efficient Object Detection
- Deformable DETR: Deformable Transformers for End-to-End Object Detection
- Simple Copy-Paste is a Strong Data Augmentation Method for Instance Segmentation
- RepVGG: Making VGG-style ConvNets Great Again
- Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
- TOOD: Task-aligned One-stage Object Detection
- Oriented R-CNN for Object Detection
Cited by
- CSFPR-RTDETR: Real-Time Small Object Detection Network for UAV Images Based on Cross-Spatial-Frequency Domain and Position Relation
- A Simple Detector with Frame Dynamics is a Strong Tracker
- FEWheat-YOLO: A Lightweight Improved Algorithm for Wheat Spike Detection
- Lightweight Rotated Object Detection Model for Pallets
- UAV Small Object Detection Algorithm Based on Dynamic Feature Aggregation and Hierarchical Attention Mechanism
- MambaNeXt-YOLO: A Hybrid State Space Model for Real-time Object Detection
- Lightweight multi-module convolutional network for efficient forest fire smoke detection
- STV2YOLO: An Improved Method for Unmanned Aerial Vehicle Time-Sensitive Target Detection in YOLOv5 Based on SwinTransformerV2
- BGR-YOLO: an obstacle detection algorithm based on multi-scale feature fusion for UAVs in low-altitude complex environments
- MFA-YOLO: a multi-feature aggregation approach for small-object detection method in drone imagery
- DIF-DETR: Dynamic Interactive Fusion Transformer with Adaptive Feature Enhancement for Efficient Aerial Small Object Detection
- AR-DETR: A lightweight RT-DETR-based framework for robust aircraft detection in complex remote sensing imagery
- AquaYOLO: A Lightweight Real-Time Detection Model for Floating Objects on Water Surfaces
- MD-YOLO: research on the innovation and performance optimization of vehicle detection technology
- FGOM-RTDETR: Far-Shore-Guided Object-Focusing Multiscale Network With Real-Time Detection Transformer for Infrared Ship Target Detection
- Domain-Adaptive Fine-Tuning of HI-Diff for Enhanced Microscopy Deblurring and Bacterial Flagellar Motor Localization
- MF-DEIM: A Multi-Scale Fusion Network for Polyp Detection
- YOLO-MDD: Addressing Inconsistent Scale Challenges in Mobile Screen Damage Detection
- A lightweight metallographic defect detection framework via structured priors and energy-aware attention under strong grain boundary interference
- Robust Sheep Face Recognition in Complex Environments: A Hybrid Approach Combining Wavelet-Aware RT-DETR and Adaptive MobileViT
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