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DOANet: Point Cloud Registration with Deep Overlap Attention

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DOANet: Point Cloud Registration with Deep Overlap Attention

Chinese Automation Congress (CAC)

作者： Haining Guan Qing Gao Baochang Zhang School of Automation Science and Electrical Engineering Beihang University Beijing China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing China

ISBN: (纸本)9781665426480

Pairwise point cloud registration is a fundamental task in 3D computer vision and various approaches have been proposed to handle this problem in recent years. Despite the fast evolution of registration algorithms, little attention has been drawn to align point cloud pairs with a low-overlap ratio (≤30%). In this paper, we propose a new neural network architecture named the DOANet, an end-to-end trainable fully convolutional neural network, to deal with the problem of registration with low overlap. In particular, we leverage sparse convolutions to extract robust and discriminative dense features, and further utilize attention mechanisms to explicitly predict the overlap region for point cloud fragments. The receptive field of our local point patches is constrained within the overlap region generated on the fly, which prevents the local point features from being contaminated by geometric information outside the overlap region. Experiments indicate the effectiveness and advantages of our method on both 3DLoMatch (all pairs under 30% overlap-ratio) and 3DMatch and illustrate obvious improvement over the existing results.

关键词： Point cloud compression Computer vision Three-dimensional displays Automation Neural networks Computer architecture Benchmark testing

Self-torqued harmonics and attosecond pulses driven by time-delayed relativistic vortex lasers

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Physical Review A 2022年第3期106卷 033515-033515页

作者： Jingwei Wang Matt Zepf Yuxin Leng Ruxin Li Sergey G. Rykovanov State Key Laboratory of High Field Laser Physics and Chinese Academy of Sciences Center for Excellence in Ultra-Intense Laser Science Shanghai Institute of Optics and Fine Mechanics Chinese Academy of Sciences Shanghai 201800 China China-Russian Belt and Road Joint Laboratory on Laser Science Shanghai 201800 China Collaborative Innovation Center of IFSA Shanghai Jiao Tong University Shanghai 200240 China Helmholtz Institute Jena Fröbelstieg 3 07743 Jena Germany Faculty of Physics and Astronomy Friedrich-Schiller-Universität Jena 07743 Jena Germany High Performance Computing and Big Data Laboratory Center for Computational and Data-Intensive Science and Engineering Skolkovo Institute of Science and Technology Moscow 121205 Russia

Light carrying time-varying orbital angular momentum (OAM) is a recently discovered type of structured electromagnetic field compared with a typical vortex field whose OAM is static. Such so-called self-torqued light is employed for manipulating the fast magnetic, topological, and quantum excitations and increasing its intensity and having access to shorter pulse durations would be of great benefit. Here we theoretically and numerically demonstrate the generation of intense self-torqued harmonics and attosecond pulses in the relativistic regime, driven by two time-delayed relativistic vortex lasers with different OAMs l1 and l2. The OAM of the nth harmonic spans nl1 to nl2, and the OAM of the attosecond pulses changes from l1 to l2. Such intense self-torqued harmonics and attosecond pulses may offer alternative possibilities in ultrafast spectroscopy.

关键词： High intensity laser-plasma interactions High-energy-density plasmas Radiation & particle generation in plasmas Ultrafast phenomena Relativistic plasmas Particle-in-cell methods Relativistic hydrodynamics

Vus from kaon semileptonic form factor in N f = 2 + 1 QCD at the physical point on (10 fm)4

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arXiv 2023年

作者： Yamazaki, Takeshi Ishikawa, Ken-Ichi Ishizuka, Naruhito Kuramashi, Yoshinobu Namekawa, Yusuke Taniguchi, Yusuke Ukita, Naoya Yoshié, Tomoteru Institute of Pure and Applied Sciences University of Tsukuba Ibaraki Tsukuba305-8571 Japan Center for Computational Sciences University of Tsukuba Ibaraki Tsukuba305-8577 Japan Core of Research for the Energetic Universe Graduate School of Advanced Science and Engineering Hiroshima University Higashi-Hiroshima739-8526 Japan Education and Research Center for Artificial Intelligence and Data Innovation Hiroshima University Higashi-Hiroshima739-8521 Japan

We present a preliminary result of the kaon semileptonic form factor calculated at the smallest lattice spacing in the PACS10 configurations, whose physical volumes are more than (10 fm)4 at the physical point. The configurations were generated using the Iwasaki gauge action and N f = 2 + 1 stout-smeared nonperturbatively O (a) improved Wilson quark action at the three lattice spacings, 0.085, 0.063, and 0.041 fm. The value of |Vus | in the continuum limit is estimated from our results including the preliminary one. We compare our result of |Vus | with the previous results and those through the kaon leptonic decay. Copyright © 2023, The Authors. All rights reserved.

关键词： Hadrons

A simple model of edit activity in Wikipedia

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arXiv 2023年

作者： Shimada, Takashi Ogushi, Fumiko Török, János Kertész, János Kaski, Kimmo Department of Systems Innovation Graduate School of Engineering The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-8656 Japan Mathematics and Informatics Center The University of Tokyo 1-3 Machikaneyama Osaka Toyonaka560-8531 Japan Center for Mathematical Modeling and Data Science Osaka University 1-3 Machikaneyama Osaka Toyonaka560-8531 Japan MTA-BME Morphodynamics Research Group Department of Theoretical Physics Budapest University of Technology and Economics Muegyetem Rkp 3 Budapest1111 Hungary Department of Network and Data Science Central European University Vienna Austria Aalto University School of Science Espoo Finland

A simple dynamical model of collective edit activity of Wikipedia articles and their content evolution is introduced. Based on the recent empirical findings, each editor in the model is characterized by an ability to make content edit, i.e., improving the article by adding content and a tendency to make maintenance edit, i.e., dealing with formal aspects and maintaining the edit flow. In addition, each article is characterized by a level of maturity as compared to a potential quality needed to comprehensively cover its topic. This model is found to reproduce the basic structure of the bipartite network between editors and articles of Wikipedia. Furthermore, the relation between the model parameters of editors and articles and the metrics of those calculated from the emergent network turns out to be robust, i.e. depending only on the rate of the introduction of new articles to the editing activity. This results provides us a way to relate observations in the real data to the hidden characteristics of editors and articles. For the nestedness of the networks, systems with weighted parameter distribution gives better match to the empirical one. This suggests the importance of high-dimensional nature of the ability of editors and quality of articles in the real system. Copyright © 2023, The Authors. All rights reserved.

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Toward Communication Optimization for Future Underwater Networking: A Survey of Reinforcement Learning-Based Approaches

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IEEE Communications Surveys and Tutorials 2024年

作者： Wang, Ziyuan Du, Jun Hou, Xiangwang Wang, Jingjing Jiang, Chunxiao Zhang, Xiao-Ping Ren, Yong Shenzhen Key Laboratory of Ubiquitous Data Enabling Shenzhen International Graduate School Tsinghua University Shenzhen518055 China Tsinghua-Berkeley Shenzhen Institute Shenzhen518055 China the Department of Electronic Engineering Tsinghua University Beijing100084 China the School of Cyber Science and Technology Beihang University Beijing100191 China Hangzhou Innovation Institute Beihang University Hangzhou310051 China Beijing National Research Center for Information Science and Technology Tsinghua University Beijing100084 China Tsinghua-Berkeley Shenzhen Institute Tsinghua University Shenzhen518055 China Network and Communication Research Center Peng Cheng Laboratory Shenzhen518055 China

—As an essential part of the 6G sea-land-air integrated network, underwater networking has attracted increasing attention and has been widely studied. The key for improving its performance is the communication optimization based on data rate, throughput, latency, reliability, spectrum utilization, and other factors impacting on the quality of service (QoS). However, the poor underwater communication environment makes it difficult to improve the communication quality of underwater networking and brings many challenges to the design of optimization schemes. In the face of complex and unknown dynamic underwater environment, the optimization schemes need to have a higher level of adaptability and intelligence, so as to carry out autonomous decision-making and multi-objective optimization under different conditions. To meet the above challenges and needs, reinforcement learning (RL) is widely used to obtain the optimal strategy for underwater communication. Nevertheless, there is still a lack of comprehensive reviews on using RL to optimize underwater communication networking. Therefore, this survey comprehensively investigates the application of RL in underwater networking to guide the optimization of underwater communication in the future and bridge this gap. Specifically, we provide an overview of RL usage processes and tools and detail its various applications in underwater communication networking, including spectrum resource allocation and development, throughput improvement and delay reduction, reliability improvement, energy saving, and energy efficiency optimization, data sensing and processing, and intelligent cluster networking. Based on the review, we further analyze the open challenges and research directions of RL-enabled underwater communication networking in the future. © 2024 IEEE.

关键词： 6G sea-land-air integrated network communication optimization quality of service reinforcement learning underwater networking

A Low-rank Matching Attention based Cross-modal Feature Fusion Method for Conversational Emotion Recognition

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arXiv 2023年

作者： Shou, Yuntao Liu, Huan Cao, Xiangyong Meng, Deyu Dong, Bo School of Computer Science and Technology The Ministry of Education Key Laboratory for Intelligent Networks and Network Security The Shaanxi Province Key Laboratory of Big Data Knowledge Engineering Xi’an Jiaotong Shaanxi Xi’an710049 China School of Computer Science and Technology Xi’an Jiaotong Shaanxi Xi’an710049 China The BigKE Joint Innovation Center SHMEEA Shanghai China School of Mathematics and Statistics Xi’an Jiaotong University Xi’an China

Conversational emotion recognition (CER) is an important research topic in human-computer interactions. Although recent advancements in transformer-based cross-modal fusion methods have shown promise in CER tasks, they tend to overlook the crucial intra-modal and inter-modal emotional interaction or suffer from high computational complexity. To address this, we introduce a novel and lightweight cross-modal feature fusion method called Low-Rank Matching Attention Method (LMAM). LMAM effectively captures contextual emotional semantic information in conversations while mitigating the quadratic complexity issue caused by the self-attention mechanism. Specifically, by setting a matching weight and calculating inter-modal features attention scores row by row, LMAM requires only one-third of the parameters of self-attention methods. We also employ the low-rank decomposition method on the weights to further reduce the number of parameters in LMAM. As a result, LMAM offers a lightweight model while avoiding overfitting problems caused by a large number of parameters. Moreover, LMAM is able to fully exploit the intra-modal emotional contextual information within each modality and integrates complementary emotional semantic information across modalities by computing and fusing similarities of intra-modal and inter-modal features simultaneously. Experimental results verify the superiority of LMAM compared with other popular cross-modal fusion methods on the premise of being more lightweight. Also, LMAM can be embedded into any existing state-of-the-art CER methods in a plug-and-play manner, and can be applied to other multi-modal recognition tasks, e.g., session recommendation and humour detection, demonstrating its remarkable generalization ability. Copyright © 2023, The Authors. All rights reserved.

关键词： Semantics

Dzyaloshinskii-Moriya interaction from unquenched orbital angular momentum

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arXiv 2023年

作者： Chen, Runze Go, Dongwook Blügel, Stefan Zhao, Weisheng Mokrousov, Yuriy Fert Beijing Institute School of Integrated Circuit Science and Engineering Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100191 China Peter Grünberg Institut Institute for Advanced Simulation Forschungszentrum Jülich and JARA Jülich52425 Germany Institute of Physics Johannes Gutenberg University Mainz Mainz55099 Germany

Orbitronics is an emerging and fascinating field that explores the utilization of the orbital degree of freedom of electrons for information processing. An increasing number of orbital phenomena are being currently discovered, with spin-orbit coupling mediating the interplay between orbital and spin effects, thus providing a wealth of control mechanisms and device applications. In this context, the orbital analog of spin Dzyaloshinskii-Moriya interaction (DMI), i.e. orbital DMI, deserves to be explored in depth, since it is believed to be capable of inducing chiral orbital structures. Here, we unveil the main features and microscopic mechanisms of the orbital DMI in a two-dimensional square lattice using a tight-binding model of t2g orbitals in combination with the Berry phase theory. This approach allows us to investigate and transparently disentangle the role of inversion symmetry breaking, strength of orbital exchange interaction and spin-orbit coupling in shaping the properties of the orbital DMI. By scrutinizing the band-resolved contributions we are able to understand the microscopic mechanisms and guiding principles behind the orbital DMI and its anisotropy in two dimensional magnetic materials, and uncover a fundamental relation between the orbital DMI and its spin counterpart, which is currently explored very intensively. The insights gained from our work contribute to advancing our knowledge of orbital-related effects and their potential applications in spintronics, providing a path for future research in the field of chiral orbitronics. Copyright © 2023, The Authors. All rights reserved.

关键词： Degrees of freedom (mechanics)

NTIRE 2023 Challenge on Light Field Image Super-Resolution: dataset, Methods and Results

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NTIRE 2023 Challenge on Light Field Image Super-Resolution: ...

2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2023

作者： Wang, Yingqian Wang, Longguang Liang, Zhengyu Yang, Jungang Timofte, Radu Guo, Yulan Jin, Kai Wei, Zeqiang Yang, Angulia Guo, Sha Gao, Mingzhi Zhou, Xiuzhuang Van Duong, Vinh Huu, Thuc Nguyen Yim, Jonghoon Jeon, Byeungwoo Liu, Yutong Cheng, Zhen Xiao, Zeyu Xu, Ruikang Xiong, Zhiwei Liu, Gaosheng Jin, Manchang Yue, Huanjing Yang, Jingyu Gao, Chen Zhang, Shuo Chang, Song Lin, Youfang Chao, Wentao Wang, Xuechun Wang, Guanghui Duan, Fuqing Xia, Wang Wang, Yan Xia, Peiqi Wang, Shunzhou Lu, Yao Cong, Ruixuan Sheng, Hao Yang, Da Chen, Rongshan Wang, Sizhe Cui, Zhenglong Chen, Yilei Lu, Yongjie Cai, Dongjun An, Ping Salem, Ahmed Ibrahem, Hatem Yagoub, Bilel Kang, Hyun-Soo Zeng, Zekai Wu, Heng National University of Defense Technology China Aviation University of Air Force China University of Würzburg Germany Eth Zürich Switzerland Sun Yat-sen University The Shenzhen Campus of Sun Yat-sen University China Bigo Technology Pte. Ltd. Singapore Smart Medical Innovation Lab Beijing University of Posts and Telecommunications China Global Explorer Ltd. Suzhou China National Engineering Research Center of Visual Technology School of Computer Science Peking University China School of Artificial Intelligence Beijing University of Posts and Telecommunications China Department of Electrical and Computer Engineering Sungkyunkwan University Korea Republic of University of Science and Technology of China China School of Electrical and Information Engineering Tianjin University China Beijing Key Lab of Traffic Data Analysis and Mining School of Computer and Information Technology Beijing Jiaotong University China Beijing Normal University China Toronto Metropolitan University Canada Beijing Institute of Technology China Shenzhen MSU-BIT University China State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University China Beihang Hangzhou Innovation Institute Yuhang China Faculty of Applied Sciences Macao Polytechnic University China School of Communication and Information Engineering Shanghai University China School of Information and Communication Engineering Chungbuk National University Korea Republic of Guangdong University of Technology China

ISBN: (纸本)9798350302493

In this report, we summarize the first NTIRE challenge on light field (LF) image super-resolution (SR), which aims at super-resolving LF images under the standard bicubic degradation with a magnification factor of 4. This challenge develops a new LF dataset called NTIRE-2023 for validation and test, and provides a toolbox called BasicLFSR to facilitate model development. Compared with single image SR, the major challenge of LF image SR lies in how to exploit complementary angular information from plenty of views with varying disparities. In total, 148 participants have registered the challenge, and 11 teams have successfully submitted results with PSNR scores higher than the baseline method LF-InterNet [1]. These newly developed methods have set new state-of-the-art in LF image SR, e.g., the winning method achieves around 1 dB PSNR improvement over the existing state-of-the-art method DistgSSR [2]. We report the solutions proposed by the participants, and summarize their common trends and useful tricks. We hope this challenge can stimulate future research and inspire new ideas in LF image SR. © 2023 IEEE.

关键词： Image enhancement

A novel in-memory computing scheme based on toggle spin torque MRAM 20

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A novel in-memory computing scheme based on toggle spin torq...

30th Great Lakes Symposium on VLSI, GLSVLSI 2020

作者： Bai, Yining Zhang, Yue Wang, Jinkai Wang, Guanda Zhang, Zhizhong Zheng, Zhenyi Zhang, Kun Zhao, Weisheng Fert Beijing Institute School of Microelectronics Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University China Nanoelectronics Science and Technology Center Hefei Innovation Research Institute Beihang University Hefei China School of Electronics Engineering Beihang University Beijing China

ISBN: (纸本)9781450379441

This paper proposes a novel in-memory computing (IMC) scheme based on toggle spin torque magnetic random access memory (TST-MRAM), called TST-IMC, which makes full use of the unique TST writing mechanism. In this scheme, all of the computing results are directly written in bit-cells without transferring data out of the memory array. Varied Boolean logic operations, such as, NAND, NOR and XOR, can be achieved by specially configuring decision cells. We can also implement three-input majority logic through replacing a decision cell with a datum cell, which can further be used to realize the carry of full-adder. By using 28 nm CMOS technology node and 50 nmdiameter TST-MRAM, we perform mixed simulations to validate the functionality of the proposed TST-IMC scheme. Simulation results show that XOR logic operation can be carried out within 4 ns at 1.8 V supply voltage while the other basic logic operations can be faster, i.e. within 2 ns. In addition, TST-IMC 33% less time and 44% energy saved comparing with existing IMC schemes. © 2020 Association for Computing Machinery.

关键词： Cells