no code implementations • 18 Mar 2024 • Xin Tang, Qian Chen, Rong Yu, Xiaohuan Li
Moreover, the resource mutual exclusion problem of dynamic task assignment has not been effectively solved.
no code implementations • 26 Apr 2023 • Xiaorui Wang, Jun Wang, Xin Tang, Peng Gao, Rui Fang, Guotong Xie
Filter pruning is widely adopted to compress and accelerate the Convolutional Neural Networks (CNNs), but most previous works ignore the relationship between filters and channels in different layers.
no code implementations • 20 Feb 2023 • Jiahuan Wang, Jun Chen, Hong Chen, Bin Gu, Weifu Li, Xin Tang
Recently, some mixture algorithms of pointwise and pairwise learning (PPL) have been formulated by employing the hybrid error metric of "pointwise loss + pairwise loss" and have shown empirical effectiveness on feature selection, ranking and recommendation tasks.
no code implementations • 21 Oct 2022 • Jun Wang, Weixun Li, Changyu Hou, Xin Tang, Yixuan Qiao, Rui Fang, Pengyong Li, Peng Gao, Guotong Xie
Contrastive learning has emerged as a powerful tool for graph representation learning.
no code implementations • 18 May 2022 • Yixuan Qiao, Hao Chen, Jun Wang, Yongquan Lai, Tuozhen Liu, Xianbin Ye, Xin Tang, Rui Fang, Peng Gao, Wenfeng Xie, Guotong Xie
This paper describes the PASH participation in TREC 2021 Deep Learning Track.
no code implementations • 30 Mar 2022 • Wenshen Xu, Mieradilijiang Maimaiti, Yuanhang Zheng, Xin Tang, Ji Zhang
Unexpectedly, MLM ignores the sentence-level training, and CL also neglects extraction of the internal info from the query.
no code implementations • 2 Dec 2021 • Xin Tang, Yongquan Lai, Ying Liu, Yuanyuan Fu, Rui Fang
In this work, we propose to model semantic and visual information jointly with a Visual-Semantic Transformer (VST).
no code implementations • 19 Jun 2021 • Jianyun Xu, Xin Tang, Jian Dou, Xu Shu, Yushi Zhu
In this technical report, we introduce the methods of HIKVISION_LiDAR_Det in the challenge of waymo open dataset real-time 3D detection.
no code implementations • 5 May 2021 • Yelin He, Xianbiao Qi, Jiaquan Ye, Peng Gao, Yihao Chen, Bingcong Li, Xin Tang, Rong Xiao
This paper presents our solution for the ICDAR 2021 Competition on Scientific Table Image Recognition to LaTeX.
no code implementations • ICCV 2021 • Jianyun Xu, Xin Tang, Yushi Zhu, Jie Sun, ShiLiang Pu
Recently, various works that attempted to introduce rotation invariance to point cloud analysis have devised point-pair features, such as angles and distances.
1 code implementation • 3 Nov 2020 • Hu Hu, Chao-Han Huck Yang, Xianjun Xia, Xue Bai, Xin Tang, Yajian Wang, Shutong Niu, Li Chai, Juanjuan Li, Hongning Zhu, Feng Bao, Yuanjun Zhao, Sabato Marco Siniscalchi, Yannan Wang, Jun Du, Chin-Hui Lee
To improve device robustness, a highly desirable key feature of a competitive data-driven acoustic scene classification (ASC) system, a novel two-stage system based on fully convolutional neural networks (CNNs) is proposed.
Ranked #1 on Acoustic Scene Classification on TAU Urban Acoustic Scenes 2019 (using extra training data)
1 code implementation • 24 Sep 2020 • Yihao Chen, Xin Tang, Xianbiao Qi, Chun-Guang Li, Rong Xiao
We conduct extensive experiments on benchmark datasets for different tasks, including node classification, link prediction, graph classification and graph regression, and confirm that the learned graph normalization leads to competitive results and that the learned weights suggest the appropriate normalization techniques for the specific task.
no code implementations • 23 Sep 2020 • Bingcong Li, Xin Tang, Xianbiao Qi, Yihao Chen, Rong Xiao
Thus, we propose a lightweight scene text recognition model named Hamming OCR.
1 code implementation • 16 Jul 2020 • Hu Hu, Chao-Han Huck Yang, Xianjun Xia, Xue Bai, Xin Tang, Yajian Wang, Shutong Niu, Li Chai, Juanjuan Li, Hongning Zhu, Feng Bao, Yuanjun Zhao, Sabato Marco Siniscalchi, Yannan Wang, Jun Du, Chin-Hui Lee
On Task 1b development data set, we achieve an accuracy of 96. 7\% with a model size smaller than 500KB.
no code implementations • 15 Jul 2020 • Xin Tang, Xu Chen, Liekang Zeng, Shuai Yu, Lin Chen
With the assistance of edge servers, user equipments (UEs) are able to run deep neural network (DNN) based AI applications, which are generally resource-hungry and compute-intensive, such that an individual UE can hardly afford by itself in real time.
no code implementations • 20 Oct 2018 • Xin Tang, Shanbo Cheng, Loc Do, Zhiyu Min, Feng Ji, Heng Yu, Ji Zhang, Haiqin Chen
Our approach is extended from a basic monolingual STS framework to a shared multilingual encoder pretrained with translation task to incorporate rich-resource language data.
no code implementations • 2 Aug 2018 • Jia-xin Cai, Xin Tang
Action recognition has attracted increasing attention from RGB input in computer vision partially due to potential applications on somatic simulation and statistics of sport such as virtual tennis game and tennis techniques and tactics analysis by video.
no code implementations • 13 Mar 2016 • Jia-xin Cai, Xin Tang, Lifang Zhang, Guocan Feng
In this paper, a discriminative two-phase dictionary learning framework is proposed for classifying human action by sparse shape representations, in which the first-phase dictionary is learned on the selected discriminative frames and the second-phase dictionary is built for recognition using reconstruction errors of the first-phase dictionary as input features.