HDPNet: A Hybrid Dynamic Perception Network for Robust Object Detection in Low-Light and Deformed Environments
Source abstract
Abstract
Achieving robust visual detection under challenging conditions such as poor illumination and target deformation remains a critical challenge for computer vision systems. Although the YOLO series of object detection algorithms excel in speed and accuracy, their performance significantly degrades under non-ideal lighting conditions. To address this issue, we propose a Hybrid Dynamic Perception Network (HDPNet), a framework specifically designed for high-precision, real-time object detection in harsh environments. HDPNet integrates three core modules into the YOLOv8n architecture to form a hybrid structure. The Dynamic Illumination-aware Module (DIM) adaptively enhances features under varying illumination through global encoding and a dual-attention mechanism, the Interactive Attention Fusion Network (IAFN) optimizes cross-modal features using a lightweight Transformer-CNN interactive architecture, and the Multi-branch Decomposition Network (MDN) captures multi-scale deformation features by combining deformable convolution and sparse Transformer. Experimental results on the self-built low-light industrial express package dataset named njpackage show that our method achieves an mAP@0.5 of 86.6%, which is 4.4% higher than the baseline YOLOv8n model, while maintaining real-time inference speed of ≥45 FPS. The proposed HDPNet not only provides an effective solution for logistics automation but also offers a robust and versatile hybrid technical framework adaptable to other vision tasks facing similar challenges.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Advanced Neural Network Applications · Human Pose and Action Recognition · Multimodal Machine Learning Applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
The Engineering and Technical College of Chengdu University of Technology, Leshan 614000, China
Intelligent Technology Application Research Center, Leshan 614000, China
College of Microelectronics and Communication Engineering, Chongqing University, Chongqing 400044, China
Funding
Open Fund of Chongqing Key Laboratory of Bio-perception & Multimodal Intelligent Information Processing · Intelligent Technology Application Research Center
References (72)
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