no code implementations • 31 Dec 2021 • Xing Wei, Yuanrui Kang, Jihao Yang, Yunfeng Qiu, Dahu Shi, Wenming Tan, Yihong Gong
First of all, we design a deformable attention in-built Transformer backbone, which learns adaptive feature representations with deformable sampling locations and dynamic attention weights.
no code implementations • 4 Jul 2021 • Hui Lin, Xiaopeng Hong, Zhiheng Ma, Xing Wei, Yunfeng Qiu, YaoWei Wang, Yihong Gong
Second, we derive a semi-balanced form of Sinkhorn divergence, based on which a Sinkhorn counting loss is designed for measure matching.
no code implementations • ICCV 2021 • Zhiheng Ma, Xiaopeng Hong, Xing Wei, Yunfeng Qiu, Yihong Gong
This paper proposes to handle the practical problem of learning a universal model for crowd counting across scenes and datasets.