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In recent years, significant progress has been made on the research of crowd counting. However, as the challenging scale variations and complex scenes existed in crowds, neither traditional convolution networks nor recent Transformer architectures wi
Externí odkaz:
http://arxiv.org/abs/2112.15509
This paper presents an end-to-end instance segmentation framework, termed SOIT, that Segments Objects with Instance-aware Transformers. Inspired by DETR \cite{carion2020end}, our method views instance segmentation as a direct set prediction problem a
Externí odkaz:
http://arxiv.org/abs/2112.11037
Multi-person pose estimation is an attractive and challenging task. Existing methods are mostly based on two-stage frameworks, which include top-down and bottom-up methods. Two-stage methods either suffer from high computational redundancy for additi
Externí odkaz:
http://arxiv.org/abs/2107.08982
Akademický článek
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Publikováno v:
2015 IEEE International Conference on Multimedia Big Data; 2015, p377-382, 6p