Zobrazeno 1 - 10
of 150
pro vyhledávání: '"Di, Xing"'
This paper presents a novel approach, called Prototype-based Self-Distillation (ProS), for unsupervised face representation learning. The existing supervised methods heavily rely on a large amount of annotated training facial data, which poses challe
Externí odkaz:
http://arxiv.org/abs/2311.01929
Autor:
Liu, Daizong, Qu, Xiaoye, Dong, Jianfeng, Zhou, Pan, Xu, Zichuan, Wang, Haozhao, Di, Xing, Lu, Weining, Cheng, Yu
This paper addresses the temporal sentence grounding (TSG). Although existing methods have made decent achievements in this task, they not only severely rely on abundant video-query paired data for training, but also easily fail into the dataset dist
Externí odkaz:
http://arxiv.org/abs/2305.04123
Autor:
Shun-Yu Deng, Mao-Xing Liu, Pin Gao, Cheng-cai Zhang, Jia-Di Xing, Kechen Guo, Kai Xu, Fei Tan, Cheng-Hai Zhang, Ming Cui, Xiang-Qian Su
Publikováno v:
BMC Surgery, Vol 24, Iss 1, Pp 1-8 (2024)
Abstract Purpose To investigate whether the mixed approach is a safe and advantageous way to operate laparoscopic right hemicolectomy. Methods A retrospective study was performed on 316 patients who underwent laparoscopic right hemicolectomy in our c
Externí odkaz:
https://doaj.org/article/b3140fb6722942bd960417121426e6aa
Given an untrimmed video, temporal sentence localization (TSL) aims to localize a specific segment according to a given sentence query. Though respectable works have made decent achievements in this task, they severely rely on dense video frame annot
Externí odkaz:
http://arxiv.org/abs/2301.01871
Autor:
Zhu, Jiahao, Liu, Daizong, Zhou, Pan, Di, Xing, Cheng, Yu, Yang, Song, Xu, Wenzheng, Xu, Zichuan, Wan, Yao, Sun, Lichao, Xiong, Zeyu
Temporal sentence grounding (TSG) aims to identify the temporal boundary of a specific segment from an untrimmed video by a sentence query. All existing works first utilize a sparse sampling strategy to extract a fixed number of video frames and then
Externí odkaz:
http://arxiv.org/abs/2301.00514
Autor:
Zhang, Huaizheng, Li, Yuanming, Xiao, Wencong, Huang, Yizheng, Di, Xing, Yin, Jianxiong, See, Simon, Luo, Yong, Lau, Chiew Tong, You, Yang
New architecture GPUs like A100 are now equipped with multi-instance GPU (MIG) technology, which allows the GPU to be partitioned into multiple small, isolated instances. This technology provides more flexibility for users to support both deep learni
Externí odkaz:
http://arxiv.org/abs/2301.00407
Autor:
Sun, Yuhua, Zhang, Tailai, Ma, Xingjun, Zhou, Pan, Lou, Jian, Xu, Zichuan, Di, Xing, Cheng, Yu, Lichao
Crowd counting is a regression task that estimates the number of people in a scene image, which plays a vital role in a range of safety-critical applications, such as video surveillance, traffic monitoring and flow control. In this paper, we investig
Externí odkaz:
http://arxiv.org/abs/2207.05641
Autor:
Liu, Daizong, Qu, Xiaoye, Wang, Yinzhen, Di, Xing, Zou, Kai, Cheng, Yu, Xu, Zichuan, Zhou, Pan
Temporal video grounding (TVG) aims to localize a target segment in a video according to a given sentence query. Though respectable works have made decent achievements in this task, they severely rely on abundant video-query paired data, which is exp
Externí odkaz:
http://arxiv.org/abs/2201.05307
Temporal sentence grounding (TSG) is crucial and fundamental for video understanding. Although the existing methods train well-designed deep networks with a large amount of data, we find that they can easily forget the rarely appeared cases in the tr
Externí odkaz:
http://arxiv.org/abs/2201.00454
Autor:
Guo, Dazhou, Ye, Xianghua, Ge, Jia, Di, Xing, Lu, Le, Huang, Lingyun, Xie, Guotong, Xiao, Jing, Liu, Zhongjie, Peng, Ling, Yan, Senxiang, Jin, Dakai
Lymph node station (LNS) delineation from computed tomography (CT) scans is an indispensable step in radiation oncology workflow. High inter-user variabilities across oncologists and prohibitive laboring costs motivated the automated approach. Previo
Externí odkaz:
http://arxiv.org/abs/2109.09271