Recent advances in deep learning for object detection
Object detection is a fundamental visual recognition problem in computer vision and has
been widely studied in the past decades. Visual object detection aims to find objects of …
been widely studied in the past decades. Visual object detection aims to find objects of …
A review of object detection based on deep learning
Y **_BiLayers_CVPR_2021_paper.pdf" data-clk="hl=ja&sa=T&oi=gga&ct=gga&cd=7&d=15732260026637551039&ei=R-mvZ6iGCtjGieoPr_Hp0AE" data-clk-atid="vwXPISQ3VNoJ" target="_blank">[PDF] thecvf.com
Deep occlusion-aware instance segmentation with overlap** bilayers
Segmenting highly-overlap** objects is challenging, because typically no distinction is
made between real object contours and occlusion boundaries. Unlike previous two-stage …
made between real object contours and occlusion boundaries. Unlike previous two-stage …
High-level semantic feature detection: A new perspective for pedestrian detection
W Liu, S Liao, W Ren, W Hu… - Proceedings of the IEEE …, 2019 - openaccess.thecvf.com
Object detection generally requires sliding-window classifiers in tradition or anchor-based
predictions in modern deep learning approaches. However, either of these approaches …
predictions in modern deep learning approaches. However, either of these approaches …
Crowd counting in the frequency domain
This paper investigates crowd counting in the frequency domain, which is a novel direction
compared to the traditional view in the spatial domain. By transforming the density map into …
compared to the traditional view in the spatial domain. By transforming the density map into …