An additional convolutional branch with a dilation rate of 4 is introduced into scale-aware RFE model (RFEM). The improved RFEM module is substituted for C2f's bottleneck of the based YOLOv8 model. The C2f-RFEM module is integrated into the backbone network to reinforce the extraction of ...
Our approach introduces a Receptive Field Enhancement (RFE) module designed to extract multi-scale pixel information and augment the receptive field for accurately detecting small faces. To address issues related to face occlusion, we introduce an attention mechanism termed the Separated and Enhancement ...
Our approach introduces a Receptive Field Enhancement (RFE) module designed to extract multi-scale pixel information and augment the receptive field for accurately detecting small faces. To address issues related to face occlusion, we introduce an attention mechanism termed the Separated and Enhancement ...
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Page, M. Rfe- nacht et al., LHAPDF6: parton density access in the LHC precision era. Eur. Phys. J. C 75, 132 (2015). arXiv:1412.7420 38. T. Sjöstrand, S. Ask, J.R. Christiansen, R. Corke, N. Desai, P. Ilten et al., An Introduction to PYTHIA 8.2. Comput. Phys. ...
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Attention to scale: Scale-aware semantic image segmentation. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, NV, USA, 27–30 June 2016; pp. 3640–3649. 9. Lin, G.; Shen, C.; Hengel AV, D.; Reid, I. Efficient piecewise training of...
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We design a Receptive Field Enhancement module called RFE to enhance receptive field of small face, and use NWD Loss to make up for the sensitivity of IoU to the location deviation of tiny objects. For face occlusion, we present an attention module named SEAM and introduce Repulsion Loss to ...
For the backbone, we employ CSPDarknet53 and integrate the RFE module into the P5 layer to facilitate the fusion of multi-scale features. Retaining the PAN structure from PAN [30], the Experiments In this part, we provide the details for experiments and results to demonstrate the ...