no code implementations • 25 Mar 2024 • Huifeng Yin, Hanle Zheng, Jiayi Mao, Siyuan Ding, Xing Liu, Mingkun Xu, Yifan Hu, Jing Pei, Lei Deng
By designing and evaluating several variants of the classic model, we systematically investigate the functional roles of key modelling components, leakage, reset, and recurrence, in leaky integrate-and-fire (LIF) based SNNs.
no code implementations • 22 Mar 2024 • Jinbo Wu, Xing Liu, Chenming Wu, Xiaobo Gao, Jialun Liu, Xinqi Liu, Chen Zhao, Haocheng Feng, Errui Ding, Jingdong Wang
We propose an optimal viewpoint selection strategy, that finds the most miniature set of viewpoints covering all the faces of a mesh.
no code implementations • 9 Mar 2024 • Pinjun Zheng, Xing Liu, Tareq Y. Al-Naffouri
To address inherent challenges including nonlinear observation function, constrained UE state, and unknown observation statistics, we develop a Riemannian manifold-based unscented Kalman filter (UKF) method.
no code implementations • 29 Feb 2024 • He Zhu, Wenjia Zhang, Nuoxian Huang, Boyang Li, Luyao Niu, Zipei Fan, Tianle Lun, Yicheng Tao, Junyou Su, Zhaoya Gong, Chenyu Fang, Xing Liu
In the field of urban planning, general-purpose large language models often struggle to meet the specific needs of planners.
1 code implementation • 27 Feb 2024 • Jiaqi Zhai, Lucy Liao, Xing Liu, Yueming Wang, Rui Li, Xuan Cao, Leon Gao, Zhaojie Gong, Fangda Gu, Michael He, Yinghai Lu, Yu Shi
Large-scale recommendation systems are characterized by their reliance on high cardinality, heterogeneous features and the need to handle tens of billions of user actions on a daily basis.
Ranked #1 on Recommendation Systems on Amazon-Book (HR@10 metric)
no code implementations • 26 Feb 2024 • Xinqi Liu, Chenming Wu, Jialun Liu, Xing Liu, Jinbo Wu, Chen Zhao, Haocheng Feng, Errui Ding, Jingdong Wang
In this paper, we present a novel method that facilitates the creation of vivid 3D Gaussian avatars from monocular video inputs (GVA).
no code implementations • 28 Dec 2023 • Pinjun Zheng, Xing Liu, Jiguang He, Gonzalo Seco-Granados, Tareq Y. Al-Naffouri
By leveraging the strong signal reception of the LEO satellite signals and capitalizing on the radio environment-reshaping capability of RISs, the integration of these two technologies presents a vision of a future where localization services transcend existing constraints.
no code implementations • 8 Dec 2023 • Yahao Shi, Yanmin Wu, Chenming Wu, Xing Liu, Chen Zhao, Haocheng Feng, Jingtuo Liu, Liangjun Zhang, Jian Zhang, Bin Zhou, Errui Ding, Jingdong Wang
This paper presents GIR, a 3D Gaussian Inverse Rendering method for relightable scene factorization.
no code implementations • 22 Nov 2023 • Weiwei Li, Xing Liu, Wei Wang, Lu Chen, Sizhe Li, Hui Fan
To address the challenge of identifying hidden danger in substations from unstructured text, a novel dynamic analysis method is proposed.
no code implementations • 19 Nov 2023 • Zihao Liu, Xing Liu, Yizhai Zhang, Zhengxiong Liu, Panfeng Huang
In this study, we propose a novel method for skill learning in robotic manipulation called Tactile Active Inference Reinforcement Learning (Tactile-AIRL), aimed at achieving efficient training.
no code implementations • 13 Sep 2023 • Lei Wang, Pinjun Zheng, Xing Liu, Tarig Ballal, Tareq Y. Al-Naffouri
The growing availability of low-Earth orbit (LEO) satellites, coupled with the anticipated widespread deployment of reconfigurable intelligent surfaces (RISs), opens up promising prospects for new localization paradigms.
no code implementations • 4 Sep 2023 • Rui Wang, Xing Liu, Yanan Wang, Haiping Huang
The recently released artificial intelligence conversational agent, ChatGPT, has gained significant attention in academia and real life.
no code implementations • 22 Aug 2023 • Pinjun Zheng, Xing Liu, Tarig Ballal, Tareq Y. Al-Naffouri
The tight fusion of the GNSS and the 5G observations results in a unique hybrid integer- and orthonormality-constrained optimization problem.
no code implementations • 30 Jul 2023 • Jinbo Wu, Xiaobo Gao, Xing Liu, Zhengyang Shen, Chen Zhao, Haocheng Feng, Jingtuo Liu, Errui Ding
In this paper, we study Text-to-3D content generation leveraging 2D diffusion priors to enhance the quality and detail of the generated 3D models.
1 code implementation • 6 Jun 2023 • Jiaqi Zhai, Zhaojie Gong, Yueming Wang, Xiao Sun, Zheng Yan, Fu Li, Xing Liu
A key component of retrieval is to model (user, item) similarity, which is commonly represented as the dot product of two learned embeddings.
1 code implementation • 28 Apr 2023 • Xing Liu, Andrew B. Duncan, Axel Gandy
Kernelized Stein discrepancy (KSD) is a score-based discrepancy widely used in goodness-of-fit tests.
no code implementations • 19 Apr 2023 • Hiwot Tadese Kassa, Paul Johnson, Jason Akers, Mrinmoy Ghosh, Andrew Tulloch, Dheevatsa Mudigere, Jongsoo Park, Xing Liu, Ronald Dreslinski, Ehsan K. Ardestani
In Deep Learning Recommendation Models (DLRM), sparse features capturing categorical inputs through embedding tables are the major contributors to model size and require high memory bandwidth.
no code implementations • 23 Mar 2023 • Pinjun Zheng, Xing Liu, Tarig Ballal, Tareq Y. Al-Naffouri
This paper considers the localization problem in a 5G-aided global navigation satellite system (GNSS) based on real-time kinematic (RTK) technique.
no code implementations • 11 Feb 2023 • Kevin H. Huang, Xing Liu, Andrew B. Duncan, Axel Gandy
We prove a convergence theorem for U-statistics of degree two, where the data dimension $d$ is allowed to scale with sample size $n$.
no code implementations • 8 Oct 2022 • Yixiang Shan, Jielong Yang, Xing Liu, Yixing Gao, Hechang Chen, Shuzhi Sam Ge
Our model solves the first issue by simultaneously learning multiple relation graphs of data samples as well as a relation network of graphs, and solves the second and the third issue by selecting important data features as well as important data sample relations.
7 code implementations • 5 Oct 2022 • Silvio Giancola, Anthony Cioppa, Adrien Deliège, Floriane Magera, Vladimir Somers, Le Kang, Xin Zhou, Olivier Barnich, Christophe De Vleeschouwer, Alexandre Alahi, Bernard Ghanem, Marc Van Droogenbroeck, Abdulrahman Darwish, Adrien Maglo, Albert Clapés, Andreas Luyts, Andrei Boiarov, Artur Xarles, Astrid Orcesi, Avijit Shah, Baoyu Fan, Bharath Comandur, Chen Chen, Chen Zhang, Chen Zhao, Chengzhi Lin, Cheuk-Yiu Chan, Chun Chuen Hui, Dengjie Li, Fan Yang, Fan Liang, Fang Da, Feng Yan, Fufu Yu, Guanshuo Wang, H. Anthony Chan, He Zhu, Hongwei Kan, Jiaming Chu, Jianming Hu, Jianyang Gu, Jin Chen, João V. B. Soares, Jonas Theiner, Jorge De Corte, José Henrique Brito, Jun Zhang, Junjie Li, Junwei Liang, Leqi Shen, Lin Ma, Lingchi Chen, Miguel Santos Marques, Mike Azatov, Nikita Kasatkin, Ning Wang, Qiong Jia, Quoc Cuong Pham, Ralph Ewerth, Ran Song, RenGang Li, Rikke Gade, Ruben Debien, Runze Zhang, Sangrok Lee, Sergio Escalera, Shan Jiang, Shigeyuki Odashima, Shimin Chen, Shoichi Masui, Shouhong Ding, Sin-wai Chan, Siyu Chen, Tallal El-Shabrawy, Tao He, Thomas B. Moeslund, Wan-Chi Siu, Wei zhang, Wei Li, Xiangwei Wang, Xiao Tan, Xiaochuan Li, Xiaolin Wei, Xiaoqing Ye, Xing Liu, Xinying Wang, Yandong Guo, YaQian Zhao, Yi Yu, YingYing Li, Yue He, Yujie Zhong, Zhenhua Guo, Zhiheng Li
The SoccerNet 2022 challenges were the second annual video understanding challenges organized by the SoccerNet team.
no code implementations • 20 May 2022 • Xing Liu, Tarig Ballal, Mohanad Ahmed, Tareq Y. Al-Naffouri
Given the characteristics of the employed nonlinear constraints, we formulate GNSS attitude determination as an optimization problem on a manifold.
1 code implementation • 7 Feb 2022 • Xing Liu, Harrison Zhu, Jean-François Ton, George Wynne, Andrew Duncan
Stein variational gradient descent (SVGD) is a deterministic particle inference algorithm that provides an efficient alternative to Markov chain Monte Carlo.
no code implementations • 4 Feb 2022 • Martha D'Eli, Hang Deng, Cedric Fraces, Krishna Garikipati, Lori Graham-Brady, Amanda Howard, Geoerge Karniadakid, Vahid Keshavarzzadeh, Robert M. Kirby, Nathan Kutz, Chunhui Li, Xing Liu, Hannah Lu, Pania Newell, Daniel O'Malley, Masa Prodanovic, Gowri Srinivasan, Alexandre Tartakovsky, Daniel M. Tartakovsky, Hamdi Tchelepi, Bozo Vazic, Hari Viswanathan, Hongkyu Yoon, Piotr Zarzycki
The "Workshop on Machine learning in heterogeneous porous materials" brought together international scientific communities of applied mathematics, porous media, and material sciences with experts in the areas of heterogeneous materials, machine learning (ML) and applied mathematics to identify how ML can advance materials research.
no code implementations • 29 Dec 2021 • Xing Liu, Tarig Ballal, Hui Chen, Tareq Y. Al-Naffouri
Attitude determination is a popular application of Global Navigation Satellite Systems (GNSS).
no code implementations • NeurIPS 2021 • Yi Ma, Xiaotian Hao, Jianye Hao, Jiawen Lu, Xing Liu, Tong Xialiang, Mingxuan Yuan, Zhigang Li, Jie Tang, Zhaopeng Meng
To address this problem, existing methods partition the overall DPDP into fixed-size sub-problems by caching online generated orders and solve each sub-problem, or on this basis to utilize the predicted future orders to optimize each sub-problem further.
no code implementations • 14 Sep 2021 • Zhijie Wang, Xing Liu, Masanori Suganuma, Takayuki Okatani
To cope with this, we propose a method that applies adversarial training to align two feature distributions in the target domain.
Ranked #1 on Domain Adaptation on Synscapes-to-Cityscapes
no code implementations • ICCV 2021 • Wenzheng Song, Masanori Suganuma, Xing Liu, Noriyuki Shimobayashi, Daisuke Maruta, Takayuki Okatani
To consider if and how well we can utilize such information stored in RAW-format images for image matching, we have created a new dataset named MID (matching in the dark).
no code implementations • 16 Aug 2021 • Ajian Liu, Chenxu Zhao, Zitong Yu, Anyang Su, Xing Liu, Zijian Kong, Jun Wan, Sergio Escalera, Hugo Jair Escalante, Zhen Lei, Guodong Guo
The threat of 3D masks to face recognition systems is increasingly serious and has been widely concerned by researchers.
no code implementations • 13 Apr 2021 • Ajian Liu, Chenxu Zhao, Zitong Yu, Jun Wan, Anyang Su, Xing Liu, Zichang Tan, Sergio Escalera, Junliang Xing, Yanyan Liang, Guodong Guo, Zhen Lei, Stan Z. Li, Du Zhang
To bridge the gap to real-world applications, we introduce a largescale High-Fidelity Mask dataset, namely CASIA-SURF HiFiMask (briefly HiFiMask).
no code implementations • 12 Apr 2021 • Dheevatsa Mudigere, Yuchen Hao, Jianyu Huang, Zhihao Jia, Andrew Tulloch, Srinivas Sridharan, Xing Liu, Mustafa Ozdal, Jade Nie, Jongsoo Park, Liang Luo, Jie Amy Yang, Leon Gao, Dmytro Ivchenko, Aarti Basant, Yuxi Hu, Jiyan Yang, Ehsan K. Ardestani, Xiaodong Wang, Rakesh Komuravelli, Ching-Hsiang Chu, Serhat Yilmaz, Huayu Li, Jiyuan Qian, Zhuobo Feng, Yinbin Ma, Junjie Yang, Ellie Wen, Hong Li, Lin Yang, Chonglin Sun, Whitney Zhao, Dimitry Melts, Krishna Dhulipala, KR Kishore, Tyler Graf, Assaf Eisenman, Kiran Kumar Matam, Adi Gangidi, Guoqiang Jerry Chen, Manoj Krishnan, Avinash Nayak, Krishnakumar Nair, Bharath Muthiah, Mahmoud khorashadi, Pallab Bhattacharya, Petr Lapukhov, Maxim Naumov, Ajit Mathews, Lin Qiao, Mikhail Smelyanskiy, Bill Jia, Vijay Rao
Deep learning recommendation models (DLRMs) are used across many business-critical services at Facebook and are the single largest AI application in terms of infrastructure demand in its data-centers.
1 code implementation • 25 Jan 2021 • Chunxing Yin, Bilge Acun, Xing Liu, Carole-Jean Wu
TT-Rec achieves 117 times and 112 times model size compression, for Kaggle and Terabyte, respectively.
no code implementations • 9 Jan 2021 • Liang Xu, Taro Hatsutani, Xing Liu, Engkarat Techapanurak, Han Zou, Takayuki Okatani
We experimentally show that this makes it possible to detect cracks from an image of one-third the resolution of images used for annotation with about the same accuracy.
1 code implementation • 17 Oct 2020 • Cole Hawkins, Xing Liu, Zheng Zhang
This paper presents a novel end-to-end framework for low-rank tensorized training of neural networks.
1 code implementation • NeurIPS 2020 • Harrison Zhu, Xing Liu, Ruya Kang, Zhichao Shen, Seth Flaxman, François-Xavier Briol
The advantages and disadvantages of this new methodology are highlighted on a set of benchmark tests including the Genz functions, and on a Bayesian survey design problem.
no code implementations • 3 Mar 2020 • Chongwei Liu, Zhihui Wang, Shijie Wang, Tao Tang, Yulong Tao, Caifei Yang, Haojie Li, Xing Liu, Xin Fan
We also propose a novel Poisson-blending Generative Adversarial Network (Poisson GAN) and an efficient object detection network (AquaNet) to address two common issues within related datasets: the class-imbalance problem and the problem of mass small object, respectively.
no code implementations • 23 Dec 2019 • Xing Liu, Xiao-Jun Wu, Zhen Liu, He-Feng Yin
The technology of face recognition has made some progress in recent years.
no code implementations • 23 Dec 2019 • Xing Liu, Xiao-Jun Wu, Zi-Qi Li
In this paper, two novel methods: 2DR1-PCA and 2DL1-PCA are proposed for face recognition.
1 code implementation • 10 Jul 2019 • Xing Liu, Masanori Suganuma, Xiyang Luo, Takayuki Okatani
The employment of convolutional neural networks has achieved unprecedented performance in the task of image restoration for a variety of degradation factors.
no code implementations • 2019 IEEE International Conference on Multimedia and Expo (ICME) 2019 • Yanshan Li, Rongjie Xia, Xing Liu, Qinghua Huang
Skeleton-based action recognition has been widely applied in intelligent video surveillance and human behavior analysis.
Ranked #88 on Skeleton Based Action Recognition on NTU RGB+D
no code implementations • 30 May 2019 • Xing Liu, Takayuki Okatani
There is another type of tasks for which what to predict is human perception itself, in which there are often individual differences.
1 code implementation • CVPR 2019 • Xing Liu, Masanori Suganuma, Zhun Sun, Takayuki Okatani
In this paper, we study design of deep neural networks for tasks of image restoration.
1 code implementation • CVPR 2019 • Masanori Suganuma, Xing Liu, Takayuki Okatani
There are many different types of distortion which affect image quality.
no code implementations • 1 Aug 2018 • Anirudh Raju, Sankaran Panchapagesan, Xing Liu, Arindam Mandal, Nikko Strom
Accurate on-device keyword spotting (KWS) with low false accept and false reject rate is crucial to customer experience for far-field voice control of conversational agents.
no code implementations • CVPR 2018 • Zhun Sun, Mete Ozay, Yan Zhang, Xing Liu, Takayuki Okatani
In this work, we address the problem of improving robustness of convolutional neural networks (CNNs) to image distortion.
no code implementations • 20 Nov 2015 • Yan Zhang, Mete Ozay, Xing Liu, Takayuki Okatani
We propose a method for integration of features extracted using deep representations of Convolutional Neural Networks (CNNs) each of which is learned using a different image dataset of objects and materials for material recognition.