Zobrazeno 1 - 10
of 49
pro vyhledávání: '"Tan Wenming"'
Autor:
Zuo Qingqiu, Sun Xiaohui, Wang Xu, Weng Xiaodong, Wang Xiaoming, Ding Youzhong, Xie Fei, Ba Jianfeng, Zou Bin, Tan Wenming, Wang Zhenghuan
Publikováno v:
International Journal for Parasitology: Parasites and Wildlife, Vol 12, Iss , Pp 242-249 (2020)
Tibetan foxes (Vulpes ferrilata) have been confirmed as the main wild definitive hosts in echinococcosis transmission in the eastern Tibetan Plateau. However, little information is available about the epidemiology in wildlife from the perspective of
Externí odkaz:
https://doaj.org/article/a4491712d671452c8c0bbabce77a2e3a
Autor:
Yang, Qiming, Zhang, Kai, Lan, Chaoxiang, Yang, Zhi, Li, Zheyang, Tan, Wenming, Xiao, Jun, Pu, Shiliang
Solid results from Transformers have made them prevailing architectures in various natural language and vision tasks. As a default component in Transformers, Layer Normalization (LN) normalizes activations within each token to boost the robustness. H
Externí odkaz:
http://arxiv.org/abs/2208.01313
Autor:
Li, Mengze, Wang, Tianbao, Zhang, Haoyu, Zhang, Shengyu, Zhao, Zhou, Miao, Jiaxu, Zhang, Wenqiao, Tan, Wenming, Wang, Jin, Wang, Peng, Pu, Shiliang, Wu, Fei
Natural language spatial video grounding aims to detect the relevant objects in video frames with descriptive sentences as the query. In spite of the great advances, most existing methods rely on dense video frame annotations, which require a tremend
Externí odkaz:
http://arxiv.org/abs/2203.08013
Autor:
Li, Zheyang, Zhang, Kai, Yang, Qiming, Lan, Chaoxiang, Zhang, Huanlong, Tan, Wenming, Xiao, Jun, Pu, Shiliang
Publikováno v:
In Knowledge-Based Systems 27 September 2024 300
This paper introduces a post-training quantization~(PTQ) method achieving highly efficient Convolutional Neural Network~ (CNN) quantization with high performance. Previous PTQ methods usually reduce compression error via performing layer-by-layer par
Externí odkaz:
http://arxiv.org/abs/2201.06376
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
Autor:
Xia, Gui-Song, Ding, Jian, Qian, Ming, Xue, Nan, Han, Jiaming, Bai, Xiang, Yang, Michael Ying, Li, Shengyang, Belongie, Serge, Luo, Jiebo, Datcu, Mihai, Pelillo, Marcello, Zhang, Liangpei, Zhou, Qiang, Yu, Chao-hui, Hu, Kaixuan, Bu, Yingjia, Tan, Wenming, Yang, Zhe, Li, Wei, Liu, Shang, Zhao, Jiaxuan, Ma, Tianzhi, Gao, Zi-han, Wang, Lingqi, Zuo, Yi, Jiao, Licheng, Meng, Chang, Wang, Hao, Wang, Jiahao, Hui, Yiming, Dong, Zhuojun, Zhang, Jie, Bao, Qianyue, Zhang, Zixiao, Liu, Fang
This report summarizes the results of Learning to Understand Aerial Images (LUAI) 2021 challenge held on ICCV 2021, which focuses on object detection and semantic segmentation in aerial images. Using DOTA-v2.0 and GID-15 datasets, this challenge prop
Externí odkaz:
http://arxiv.org/abs/2108.13246
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
Autor:
Qiao, Liang, Li, Zaisheng, Cheng, Zhanzhan, Zhang, Peng, Pu, Shiliang, Niu, Yi, Ren, Wenqi, Tan, Wenming, Wu, Fei
Table structure recognition is a challenging task due to the various structures and complicated cell spanning relations. Previous methods handled the problem starting from elements in different granularities (rows/columns, text regions), which someho
Externí odkaz:
http://arxiv.org/abs/2105.06224