Autonomous driving paper index
Next-Generation Small Object Detection with GSO-YOLOv8 and Generative AI
One-line summary
In order to address this problem, we introduce Generative Small Object YOLOv8 (GSO-YOLOv8), which expands YOLOv8x by adding a Generative Data Augmentation (GDA) module in addition to diffusion and GAN-based synthesis.
Engineering notes
Key topics: autonomous driving, object detection. See the paper for implementation details and experimental results.
Chinese explanation / 中文解读
中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。
Original abstract
Due to the scale variation, occlusion, and salient nature of large objects in feature maps, small object detection remains a difficult problem in computer vision. Conventional detectors like Faster R-CNN, SSD, and YOLO are less useful in the domains of autonomous driving, surveillance, medical imaging, and remote sensing because they are better at detecting medium-sized or large-sized objects than fine-grained small targets. In order to address this problem, we introduce Generative Small Object YOLOv8 (GSO-YOLOv8), which expands YOLOv8x by adding a Generative Data Augmentation (GDA) module in addition to diffusion and GAN-based synthesis. The suggested GDA can produce realistic small-object instances.
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