8 citations · 9 across the 3 of their papers we have counts for
3 papers
cs.CV2022★ 1 cited
Unified Normalization for Accelerating and Stabilizing Transformers
Qiming Yang, Kai Zhang, Chaoxiang Lan +5
Solid results from Transformers have made them prevailing architectures in various natural language and vision tasks. As a default component in Transformers, Layer Normalization (L…
cs.CV2021★ 8 cited
Scene-Adaptive Attention Network for Crowd Counting
Xing Wei, Yuanrui Kang, Jihao Yang +4
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 tr…
cs.CV2021
SOIT: Segmenting Objects with Instance-Aware Transformers
Xiaodong Yu, Dahu Shi, Xing Wei +3
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 m…