no code implementations • 14 Mar 2024 • Xihan Li, Xing Li, Lei Chen, Xing Zhang, Mingxuan Yuan, Jun Wang
Then, can circuits also be mastered by a a sufficiently large "circuit model", which can conquer electronic design tasks by simply predicting the next logic gate?
no code implementations • 5 Jan 2024 • Yang Yang, Yury Kartynnik, Yunpeng Li, Jiuqiang Tang, Xing Li, George Sung, Matthias Grundmann
We present StreamVC, a streaming voice conversion solution that preserves the content and prosody of any source speech while matching the voice timbre from any target speech.
no code implementations • 19 Oct 2023 • Yiming Wang, Qian Huang, Bin Tang, Huashan Sun, Xing Li
In addition, most approaches ignore the spatial and channel redundancy.
1 code implementation • 22 Aug 2023 • Zhihai Wang, Lei Chen, Jie Wang, Xing Li, Yinqi Bai, Xijun Li, Mingxuan Yuan, Jianye Hao, Yongdong Zhang, Feng Wu
In particular, we notice that the runtime of the Resub and Mfs2 operators often dominates the overall runtime of LS optimization processes.
no code implementations • 24 Jul 2023 • Beiya Dai, Xing Li, Qunyi Xie, Yulin Li, Xiameng Qin, Chengquan Zhang, Kun Yao, Junyu Han
To produce a comprehensive evaluation of MataDoc, we propose a novel benchmark ArbDoc, mainly consisting of document images with arbitrary boundaries in four typical scenarios.
1 code implementation • 7 Apr 2023 • Yiyuan Yang, Rongshang Li, Qiquan Shi, Xijun Li, Gang Hu, Xing Li, Mingxuan Yuan
This paper proposes a novel Stream-Graph neural network-based Data Prefetcher (SGDP).
1 code implementation • 29 Mar 2023 • Xinxin Hu, Haotian Chen, Junjie Zhang, Hongchang Chen, Shuxin Liu, Xing Li, Yahui Wang, xiangyang xue
Extensive experiments on two real-world telecom fraud detection datasets demonstrate that our proposed method is effective for the graph imbalance problem, outperforming the state-of-the-art GNNs and GNN-based fraud detectors.
1 code implementation • 28 Mar 2023 • Xinxin Hu, Haotian Chen, Hongchang Chen, Shuxin Liu, Xing Li, Shibo Zhang, Yahui Wang, xiangyang xue
But the imbalance problem in the aforementioned data, which could severely hinder the effectiveness of fraud detectors based on graph neural networks(GNN), has hardly been addressed in previous work.
no code implementations • CVPR 2023 • Zhibo Rao, Bangshu Xiong, Mingyi He, Yuchao Dai, Renjie He, Zhelun Shen, Xing Li
Experimental results on multi-datasets show that: (1) our method can be easily plugged into the current various stereo matching models to improve generalization performance; (2) our method can reduce the significant volatility of generalization performance among different training epochs; (3) we find that the current methods prefer to choose the best results among different training epochs as generalization performance, but it is impossible to select the best performance by ground truth in practice.
no code implementations • 6 Dec 2022 • Jianchuan Chen, Wentao Yi, Tiantian Wang, Xing Li, Liqian Ma, Yangyu Fan, Huchuan Lu
The integrated features acting as the latent code are anchored to the SMPLX mesh in the canonical space.
no code implementations • 13 Oct 2022 • Xing Li, Manuel Baum, Oliver Brock
We introduce a Learning from Demonstration (LfD) approach for contact-rich manipulation tasks with articulated mechanisms.
no code implementations • 11 Jun 2022 • Jingcheng Zhou, Wei Wei, Xing Li, Bowen Pang, Zhiming Zheng
Deep learning utilizing deep neural networks (DNNs) has achieved a lot of success recently in many important areas such as computer vision, natural language processing, and recommendation systems.
1 code implementation • 16 Nov 2021 • Xing Li, Qian Huang, Zhijian Wang, Zhenjie Hou, Tianjin Yang, Zhuang Miao
Instead of capturing spatio-temporal local structures, SequentialPointNet encodes the temporal evolution of static appearances to recognize human actions.
1 code implementation • 9 Nov 2021 • Yuzhe Gao, Xing Li, Jiajian Zhang, Yu Zhou, Dian Jin, Jing Wang, Shenggao Zhu, Xiang Bai
We leverage a Siamese ComplementaryModule to fully exploit the continuity characteristic of the textinstances in the temporal dimension, which effectively alleviatesthe missed detection of the text instances, and hence ensuresthe completeness of each text trajectory.
1 code implementation • 17 Feb 2021 • Xing Li, Haichun Yang, Jiaxin He, Aadarsh Jha, Agnes B. Fogo, Lee E. Wheless, Shilin Zhao, Yuankai Huo
Reducing outcome variance is an essential task in deep learning based medical image analysis.
no code implementations • 19 Jan 2021 • Chang Li, Qian Huang, Xing Li, Qianhan Wu
We employ depth motion images (DMI) as the templates to generate the multi-scale static representation of actions.
no code implementations • 2 Jan 2021 • Xing Li, Wei Wei, Xiangnan Feng, Zhiming Zheng
Graphs are often used to organize data because of their simple topological structure, and therefore play a key role in machine learning.
no code implementations • 31 Jul 2020 • Xing Li, Wei Wei, Xiangnan Feng, Xue Liu, Zhiming Zheng
The graph structure is a commonly used data storage mode, and it turns out that the low-dimensional embedded representation of nodes in the graph is extremely useful in various typical tasks, such as node classification, link prediction , etc.
no code implementations • 11 Jul 2020 • Sascha Rosbach, Xing Li, Simon Großjohann, Silviu Homoceanu, Stefan Roth
Furthermore, the temporal attention mechanism learns persistent interaction with other vehicles over an extended planning horizon.
no code implementations • 7 Dec 2019 • Sascha Rosbach, Vinit James, Simon Großjohann, Silviu Homoceanu, Xing Li, Stefan Roth
In this work, we propose a deep learning approach based on inverse reinforcement learning that generates situation-dependent reward functions.
3 code implementations • ACL 2019 • Mingbo Ma, Liang Huang, Hao Xiong, Renjie Zheng, Kaibo Liu, Baigong Zheng, Chuanqiang Zhang, Zhongjun He, Hairong Liu, Xing Li, Hua Wu, Haifeng Wang
Simultaneous translation, which translates sentences before they are finished, is useful in many scenarios but is notoriously difficult due to word-order differences.
no code implementations • 23 Jun 2017 • Xiaojun Chen, Lu Xu, Xing Li, Jan Egger
Patient-specific cranial implants are important and necessary in the surgery of cranial defect restoration.