1 code implementation • 4 Apr 2022 • Shuang Liang, Yinan Zou, Yong Zhou
Joint activity detection and channel estimation (JADCE) for grant-free random access is a critical issue that needs to be addressed to support massive connectivity in IoT networks.
1 code implementation • 1 Mar 2022 • Jinlai Zhang, Weiming Li, Shuang Liang, Hao Wang, Jihong Zhu
We also introduce a new U6DA-Linemod dataset for robustness study of the 6D pose estimation task.
no code implementations • 12 Dec 2021 • Weilin Liu, Ye Mu, Chao Yu, Xuefei Ning, Zhong Cao, Yi Wu, Shuang Liang, Huazhong Yang, Yu Wang
These scenarios indeed correspond to the vulnerabilities of the under-test driving policies, thus are meaningful for their further improvements.
no code implementations • 20 Aug 2021 • Shuang Liang, Yuanming Shi, Yong Zhou
Although an enhanced estimation performance in terms of the mean squared error (MSE) can be achieved, the weighted $l_1$-norm minimization algorithm is still a convex relaxation of the original group-sparse matrix estimation problem, yielding a suboptimal solution.
no code implementations • 1 Aug 2021 • Kai Wu, Vinit Kumar Chugh, Venkatramana D. Krishna, Arturo di Girolamo, Yongqiang Andrew Wang, Renata Saha, Shuang Liang, Maxim C-J Cheeran, Jian-Ping Wang
With the ongoing global pandemic of coronavirus disease 2019 (COVID-19), there is an increasing quest for more accessible, easy-to-use, rapid, inexpensive, and high accuracy diagnostic tools.
no code implementations • 8 Jul 2021 • Shuang Liang
In this paper, we present a hybrid deep learning framework named CTNet which combines convolutional neural network and transformer together for the detection of COVID-19 via 3D chest CT images.
no code implementations • 4 Mar 2021 • Jia-Xing Zhang, Lu Yang, Shuang Liang, Wei Chen, Qiang-Hua Wang
We study the possibility to realize Majorana zero mode that's robust and may be easily manipulated for braiding in quantum computing in the ground state of the Kitaev model in this work.
Strongly Correlated Electrons
1 code implementation • 25 Nov 2020 • Xuefei Ning, Changcheng Tang, Wenshuo Li, Songyi Yang, Tianchen Zhao, Niansong Zhang, Tianyi Lu, Shuang Liang, Huazhong Yang, Yu Wang
Neural Architecture Search (NAS) has received extensive attention due to its capability to discover neural network architectures in an automated manner.
no code implementations • 21 Nov 2020 • Tianchen Zhao, Xuefei Ning, Xiangsheng Shi, Songyi Yang, Shuang Liang, Peng Lei, Jianfei Chen, Huazhong Yang, Yu Wang
We also design the micro-level search space to strengthen the information flow for BNN.
no code implementations • 28 Sep 2020 • Xuefei Ning, Wenshuo Li, Zixuan Zhou, Tianchen Zhao, Shuang Liang, Yin Zheng, Huazhong Yang, Yu Wang
A major challenge in NAS is to conduct a fast and accurate evaluation of neural architectures.
no code implementations • 18 Sep 2020 • Siyuan Lu, Meiqi Wang, Shuang Liang, Jun Lin, Zhongfeng Wang
Designing hardware accelerators for deep neural networks (DNNs) has been much desired.
1 code implementation • NeurIPS 2021 • Xuefei Ning, Changcheng Tang, Wenshuo Li, Zixuan Zhou, Shuang Liang, Huazhong Yang, Yu Wang
Conducting efficient performance estimations of neural architectures is a major challenge in neural architecture search (NAS).
no code implementations • 11 Apr 2019 • Huawei Wei, Shuang Liang, Yichen Wei
Recently, 3D face reconstruction and face alignment tasks are gradually combined into one task: 3D dense face alignment.
no code implementations • 20 Feb 2019 • Yu Xing, Shuang Liang, Lingzhi Sui, Xijie Jia, Jiantao Qiu, Xin Liu, Yushun Wang, Yu Wang, Yi Shan
On the Xilinx ZU2 @330 MHz and ZU9 @330 MHz, we achieve equivalently state-of-the-art performance on our benchmarks by na\"ive implementations without optimizations, and the throughput is further improved up to 1. 26x by leveraging heterogeneous optimizations in DNNVM.
no code implementations • CVPR 2018 • Xiangyun Zhao, Shuang Liang, Yichen Wei
In this work, we present a novel and effective framework to facilitate object detection with the instance-level segmentation information that is only supervised by bounding box annotation.
2 code implementations • ECCV 2018 • Xiao Sun, Bin Xiao, Fangyin Wei, Shuang Liang, Yichen Wei
State-of-the-art human pose estimation methods are based on heat map representation.
Ranked #19 on
Pose Estimation
on MPII Human Pose
1 code implementation • ICCV 2017 • Xiao Sun, Jiaxiang Shang, Shuang Liang, Yichen Wei
A central problem is that the structural information in the pose is not well exploited in the previous regression methods.
no code implementations • 17 Sep 2016 • Xingyi Zhou, Xiao Sun, Wei zhang, Shuang Liang, Yichen Wei
In this work, we propose to directly embed a kinematic object model into the deep neutral network learning for general articulated object pose estimation.
no code implementations • 5 Jul 2016 • Luwei Yang, Ligen Zhu, Yichen Wei, Shuang Liang, Ping Tan
Previous part-based attribute recognition approaches perform part detection and attribute recognition in separate steps.
no code implementations • CVPR 2015 • Chaoyang Wang, Long Zhao, Shuang Liang, Liqing Zhang, Jinyuan Jia, Yichen Wei
Hierarchical segmentation based object proposal methods have become an important step in modern object detection paradigm.
no code implementations • CVPR 2015 • Xiao Sun, Yichen Wei, Shuang Liang, Xiaoou Tang, Jian Sun
We extends the previous 2D cascaded object pose regression work [9] in two aspects so that it works better for 3D articulated objects.
no code implementations • CVPR 2014 • Wangjiang Zhu, Shuang Liang, Yichen Wei, Jian Sun
However, their usage of boundary prior is very simple, fragile, and the integration with other cues is mostly heuristic.