<p>To address the challenges of diverse defect shapes, small defect sizes, and real-time detection on ceramic tile surfaces, this paper proposes an efficient anchor-free detector that integrates adaptive receptive fields and feature enhancement. First, the anchor-free YOLOv8 is proposed as the detection framework to eliminate the need for setting anchor-related hyperparameters, thus avoiding their impact on performance. Second, an adaptive receptive field module (ARFM) is introduced, which extracts defect features from multiple scales through constructing several parallel branches and fuses the feature maps from different receptive fields, thereby dynamically adjusting the receptive field to detect various defects. Finally, a feature enhancement module (FEM) is added to the neck part, enhancing feature representation from both global and spatial dimensions to reduce feature information loss and improve defect detection performance. Experiments show that our detector achieves a mean average precision of 70.4%, an improvement of 6.1% over YOLOv8, while maintaining a high detection speed of 121.2 frames per second. This performance surpasses the state-of-the-art detection methods. These results indicate that our proposed model can achieve satisfactory defect detection performance, meeting the industry’s real-time detection needs.</p>