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SED-MVS: Segmentation-Driven and Edge-Aligned Deformation Multi-View Stereo with Depth Restoration and Occlusion Constraint

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IEEE Transactions on Circuits and Systems for Video Technology 2025年

作者： Yuan, Zhenlong Yang, Zhidong Cai, Yujun Wu, Kuangxin Liu, Mufan Zhang, Dapeng Jiang, Hao Li, Zhaoxin Wang, Zhaoqi Chinese Academy of Sciences Institute of Computing Technology Beijing100190 China School of Electrical Engineering and Computer Science Australia Hunan Police Academy Information Technology Department Changsha410100 China Shanghai Jiao Tong University Cooperative MediaNet Innovation Center Shanghai200240 China Lanzhou University DSLAB School of Information Science and Engineering 730000 China Ministry of Agriculture and Rural Affairs Agricultural Information Institute Chinese Academy of Agricultural Sciences Key Laboratory of Agricultural Big Data 100081 China

Recently, patch-deformation methods have exhibited significant effectiveness in multi-view stereo owing to the deformable and expandable patches in reconstructing textureless areas. However, existing approaches neglect to address the problem of deformation instability caused by easily overlooked edge-skipping, potentially leading to matching distortions, thus leaving room for further improvement. To fill this gap, we propose SED-MVS, which adopts panoptic segmentation and multi-trajectory diffusion strategy for segmentation-driven and edge-aligned patch deformation. Specifically, to prevent unanticipated edge-skipping, we first employ SAM2 for panoptic segmentation as depth-edge guidance to guide patch deformation, followed by multi-trajectory diffusion strategy to ensure patches are comprehensively aligned with depth edges. Moreover, to avoid potential inaccuracy of random initialization, we combine both sparse points from LoFTR and monocular depth map from DepthAnything V2 to restore reliable and realistic depth map for initialization and supervised guidance. Finally, we integrate the segmentation image with the monocular depth map to exploit inter-instance occlusion relationship, then further regard them as occlusion map to implement two distinct edge constraint, thereby facilitating occlusion-aware patch deformation. Extensive results on ETH3D, Tanks & Temples, BlendedMVS, Strecha and DL3DV-10K datasets validate the state-of-the-art performance and robust generalization capability of our proposed method. © 1991-2012 IEEE.

关键词： Image segmentation

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Multistage model for robust face alignment using deep neural networks

arXiv

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arXiv 2020年

作者： Wang, Huabin Cheng, Rui Zhou, Jian Tao, Liang Kwan, Hon Keung MOE Key Laboratory of Intelligent Computing and Signal Processing School of Computer Science and Technology Anhui University Hefei Anhui230601 China Department of Electrical and Computer Engineering University of Windsor WindsorONN9B 3P4 Canada

An ability to generalize unconstrained conditions such as severe occlusions and large pose variations remains a challenging goal to achieve in face alignment. In this paper, a multistage model based on deep neural networks is proposed which takes advantage of spatial transformer networks, hourglass networks and exemplar-based shape constraints. First, a spatial transformer - generative adversarial network which consists of convolutional layers and residual units is utilized to solve the initialization issues caused by face detectors, such as rotation and scale variations, to obtain improved face bounding boxes for face alignment. Then, stacked hourglass network is employed to obtain preliminary locations of landmarks as well as their corresponding scores. In addition, an exemplar-based shape dictionary is designed to determine landmarks with low scores based on those with high scores. By incorporating face shape constraints, misaligned landmarks caused by occlusions or cluttered backgrounds can be considerably improved. Extensive experiments based on challenging benchmark datasets are performed to demonstrate the superior performance of the proposed method over other state-of-the-art methods. Copyright © 2020, The Authors. All rights reserved.

关键词： Deep neural networks

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Protein structured reservoir computing for spike-based pattern recognition

arXiv

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arXiv 2020年

作者： Tsakalos, Karolos-Alexandros Sirakoulis, Georgios Ch. Adamatzky, Andrew Smith, Jim Department of Electrical and Computer Engineering Democritus University of Thrace Xanthi Greece Unconventional Computing Laboratory University of the West of England BristolBS16 1QY United Kingdom Computer Science Research Centre University of the West of England Xanthi Greece

Nowadays we witness a miniaturisation trend in the semiconductor industry backed up by groundbreaking discoveries and designs in nanoscale characterisation and fabrication. To facilitate the trend and produce ever smaller, faster and cheaper computing devices, the size of nanoelectronic devices is now reaching the scale of atoms or molecules - a technical goal undoubtedly demanding for novel devices. Following the trend, we explore an unconventional route of implementing reservoir computing on a single protein molecule and introduce neuromorphic connectivity with a small-world networking property. We have chosen Izhikevich spiking neurons as elementary processors, corresponding to the atoms of verotoxin protein, and its molecule as a 'hardware' architecture of the communication networks connecting the processors. We apply on a single readout layer, various training methods in a supervised fashion to investigate whether the molecular structured Reservoir computing (RC) system is capable to deal with machine learning benchmarks. We start with the Remote Supervised Method, based on Spike-Timing-Dependent-Plasticity, and carry on with linear regression and scaled conjugate gradient back-propagation training methods. The RC network is evaluated as a proof-of-concept on the handwritten digit images from the standard MNIST and the extended MNIST datasets and demonstrates acceptable classification accuracies in comparison with other similar approaches. Copyright © 2020, The Authors. All rights reserved.

关键词： Proteins

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Quantum engineering with hybrid magnonics systems and materials

arXiv

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arXiv 2021年

作者： Awschalom, D.D. Du, C.H.R. He, R. Heremans, F.J. Hoffmann, A. Hou, J.T. Kurebayashi, H. Li, Y. Liu, L. Novosad, V. Sklenar, J. Sullivan, S.E. Sun, D. Tang, H. Tiberkevich, V. Trevillian, C. Tsen, A.W. Weiss, L.R. Zhang, W. Zhang, X. Zhao, L. Zollitsch, C.W. Pritzker School of Molecular Engineering University of Chicago ChicagoIL United States Materials Science Division Center for Molecular Engineering Argonne National Laboratory LemontIL United States Department of Physics University of California San Diego San DiegoCA92093 United States Department of Electrical and Computer Engineering Texas Tech University LubbockTX79409 United States Materials Research Laboratory Department of Materials Science and Engineering University of Illinois at Urbana-Champaign UrbanaIL61801 United States Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA United States London Centre for Nanotechnology University College London 17-19 Gordon Street LondonWCH1 0AH United Kingdom Materials Science Division Argonne National Laboratory LemontIL United States Department of Physics and Astronomy Wayne State University DetroitMI48201 United States Department of Physics North Carolina State University RaleighNC27695 United States Department of Electrical Engineering Yale University New HavenCT United States Department of Physics Oakland University MI48309 United States Institute for Quantum Computing Department of Chemistry University of Waterloo WaterlooON Canada Center for Nanoscale Materials Argonne National Laboratory LemontIL United States Department of Physics University of Michigan Ann ArborMI48109 United States

Quantum technology has made tremendous strides over the past two decades with remarkable advances in materials engineering, circuit design and dynamic operation. In particular, the integration of different quantum modules has benefited from hybrid quantum systems, which provide an important pathway for harnessing the different natural advantages of complementary quantum systems and for engineering new functionalities. This review focuses on the current frontiers with respect to utilizing magnetic excitatons or magnons for novel quantum functionality. Magnons are the fundamental excitations of magnetically ordered solid-state materials and provide great tunability and flexibility for interacting with various quantum modules for integration in diverse quantum systems. The concomitant rich variety of physics and material selections enable exploration of novel quantum phenomena in materials science and engineering. In addition, the relative ease of generating strong coupling and forming hybrid dynamic systems with other excitations makes hybrid magnonics a unique platform for quantum engineering. We start our discussion with circuit-based hybrid magnonic systems, which are coupled with microwave photons and acoustic phonons. Subsequently, we are focusing on the recent progress of magnon-magnon coupling within confined magnetic systems. Next we highlight new opportunities for understanding the interactions between magnons and nitrogen-vacancy centers for quantum sensing and implementing quantum interconnects. Lastly, we focus on the spin excitations and magnon spectra of novel quantum materials investigated with advanced optical characterization. Copyright © 2021, The Authors. All rights reserved.

关键词： Quantum optics

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Crosslink-net: Double-branch encoder segmentation network via fusing vertical and horizontal convolutions

arXiv

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arXiv 2021年

作者： Yu, Qian Qi, Lei Zhou, Luping Wang, Lei Yin, Yilong Shi, Yinghuan Wang, Wuzhang Gao, Yang School of Data and Computer Science Shandong Women's University Jinan250300 China The State Key Laboratory for Novel Software Technology Nanjing University Nanjing210023 China School of Computer Science and Engineering Southeast University Nanjing211189 China The School of Electrical and Information Engineering University of Sydney NSW2006 Australia The School of Computing and Information Technology University of Wollongong WollongongNSW2522 Australia The School of Soft Shandong University Jinan250100 China Department of Respiratory and Critical Care Medicine Shandong Chest Hospital Jinan250013 China

Accurate image segmentation plays a crucial role in medical image analysis, yet it faces great challenges of various shapes, diverse sizes, and blurry boundaries. To address these difficulties, square kernel-based encoder-decoder architecture has been proposed and widely used, but its performance remains still unsatisfactory. To further cope with these challenges, we present a novel double-branch encoder architecture. Our architecture is inspired by two observations: 1) Since the discrimination of features learned via square convolutional kernels needs to be further improved, we propose to utilize non-square vertical and horizontal convolutional kernels in the double-branch encoder, so features learned by the two branches can be expected to complement each other. 2) Considering that spatial attention can help models to better focus on the target region in a large-sized image, we develop an attention loss to further emphasize the segmentation on small-sized targets. Together, the above two schemes give rise to a novel double-branch encoder segmentation framework for medical image segmentation, namely Crosslink-Net. The experiments validate the effectiveness of our model on four datasets. The code is released at https://***/Qianyu1226/*** Codes 68T07 Copyright © 2021, The Authors. All rights reserved.

关键词： Convolution

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Framing image registration as a landmark detection problem for label-noise-aware task representation (HitR)

arXiv

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arXiv 2023年

作者： Waldmannstetter, Diana Ezhov, Ivan Wiestler, Benedikt Campi, Francesco Kukuljan, Ivan Ehrlich, Stefan Vinayahalingam, Shankeeth Baheti, Bhakti Chakrabarty, Satrajit Baid, Ujjwal Bakas, Spyridon Schwarting, Julian Metz, Marie Kirschke, Jan S. Rueckert, Daniel Heckemann, Rolf A. Piraud, Marie Menze, Bjoern H. Kofler, Florian Department of Computer Science TUM School of Computation Information and Technology Technical University of Munich Munich Germany Department of Quantitative Biomedicine University of Zurich Zurich Switzerland Department of Diagnostic and Interventional Neuroradiology School of Medicine Klinikum rechts der Isar Technical University of Munich Germany Helmholtz AI Helmholtz Munich Neuherberg Germany TranslaTUM - Central Institute for Translational Cancer Research Technical University of Munich Germany Healthcare Technologies SETLabs Research Munich Germany Department of Oral and Maxillofacial Surgery Radboud University Nijmegen Medical Centre Nijmegen Netherlands Division of Computational Pathology Department of Pathology and Laboratory Medicine School of Medicine Indiana University IndianapolisIN United States Department of Electrical and Systems Engineering Washington University in St.Louis St. LouisMO United States Artificial Intelligence in Healthcare and Medicine Technical University of Munich Munich Germany Department of Computing Imperial College London London United Kingdom Department of Medical Radiation Sciences University of Gothenburg Gothenburg Sweden

Accurate image registration is pivotal in bio-medical image analysis, where selecting suitable registration algorithms demands careful consideration. While numerous algorithms are available, the evaluation metrics to assess their performance have remained relatively static. This study addresses this challenge by introducing a novel evaluation metric termed Landmark Hit Rate (HitR), which focuses on the clinical relevance of image registration accuracy. Unlike traditional metrics such as Target Registration Error, which emphasize sub-resolution differences, HitR considers whether registration algorithms successfully position landmarks within defined confidence zones. This paradigm shift acknowledges the inherent annotation noise in medical images, allowing for more meaningful assessments. To equip HitR with label-noise-awareness, we propose defining these confidence zones based on an Inter-rater Variance analysis. Consequently, hit rate curves are computed for varying landmark zone sizes, enabling performance measurement for a task-specific level of accuracy. Our approach offers a more realistic and meaningful assessment of image registration algorithms, reflecting their suitability for clinical and biomedical applications. Copyright © 2023, The Authors. All rights reserved.

关键词： Medical imaging

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Systematic Improvements in Transmon Qubit Coherence Enabled by Niobium Surface Encapsulation

arXiv

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arXiv 2023年

作者： Bal, Mustafa Murthy, Akshay A. Zhu, Shaojiang Crisa, Francesco You, Xinyuan Huang, Ziwen Roy, Tanay Lee, Jaeyel van Zanten, David Pilipenko, Roman Nekrashevich, Ivan Lunin, Andrei Bafia, Daniel Krasnikova, Yulia Kopas, Cameron J. Lachman, Ella O. Miller, Duncan Mutus, Josh Y. Reagor, Matthew J. Cansizoglu, Hilal Marshall, Jayss Pappas, David P. Vu, Kim Yadavalli, Kameshwar Oh, Jin-Su Zhou, Lin Kramer, Matthew J. Lecocq, Florent Q. Goronzy, Dominic P. Torres-Castanedo, Carlos G. Pritchard, Graham Dravid, Vinayak P. Rondinelli, James M. Bedzyk, Michael J. Hersam, Mark C. Zasadzinski, John Koch, Jens Sauls, James A. Romanenko, Alexander Grassellino, Anna BataviaIL60510 United States Rigetti Computing BerkeleyCA94710 United States Ames Laboratory U.S. Department of Energy AmesIA50011 United States National Institute of Standards and Technology BoulderCO United States Department of Materials Science and Engineering Northwestern University EvanstonIL60208 United States The NUANCE Center Northwestern University EvanstonIL60208 United States International Institute of Nanotechnology Northwestern University EvanstonIL60208 United States Department of Chemistry Northwestern University EvanstonIL60208 United States Department of Electrical and Computer Engineering Northwestern University EvanstonIL60208 United States Department of Physics Illinois Institute of Technology ChicagoIL60616 United States Department of Physics and Astronomy Northwestern University EvanstonIL60208 United States Center for Applied Physics and Superconducting Technologies Northwestern University EvanstonIL60208 United States Hearne Institute of Theoretical Physics Department of Physics and Astronomy Louisiana State University Baton RougeLA70803 United States

We present a novel transmon qubit fabrication technique that yields systematic improvements in T1 relaxation times. We fabricate devices using an encapsulation strategy that involves passivating the surface of niobium and thereby preventing the formation of its lossy surface oxide. By maintaining the same superconducting metal and only varying the surface structure, this comparative investigation examining different capping materials, such as tantalum, aluminum, titanium nitride, and gold, and film substrates across different qubit foundries definitively demonstrates the detrimental impact that niobium oxides have on the coherence times of superconducting qubits, compared to native oxides of tantalum, aluminum or titanium nitride. Our surface-encapsulated niobium qubit devices exhibit T1 relaxation times 2 to 5 times longer than baseline niobium qubit devices with native niobium oxides. When capping niobium with tantalum, we obtain median qubit lifetimes above 300 microseconds, with maximum values up to 600 microseconds, that represent the highest lifetimes to date for superconducting qubits prepared on both sapphire and silicon. Our comparative structural and chemical analysis suggests why amorphous niobium oxides may induce higher losses compared to other amorphous oxides. These results are in line with high-accuracy measurements of the niobium oxide loss tangent obtained with ultra-high Q superconducting radiofrequency (SRF) cavities. This new surface encapsulation strategy enables even further reduction of dielectric losses via passivation with ambient-stable materials, while preserving fabrication and scalable manufacturability thanks to the compatibility with silicon processes. © 2023, CC BY.

关键词： Fabrication

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Ultrathin active polarization-selective metasurface at X-band frequencies

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Physical Review B 2019年第7期100卷 075131-075131页

作者： Josip Lončar Anthony Grbic Silvio Hrabar Faculty of Electrical Engineering and Computing University of Zagreb Unska 3 10000 Zagreb Croatia Radiation Laboratory Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor Michigan 48109-2122 USA

An ultrathin active polarization-selective metasurface is designed and optimized for operation in the X band. The metasurface leverages the design of a previously reported passive polarization converting metasurface. Similar to the passive polarization converter, the proposed active metasurface consists of three patterned metallic sheets. Its bottom sheet is modified and populated with ultrawideband, unconditionally stable amplifiers and corresponding biasing networks. The metasurface provides over 35 dB of input-output isolation achieved through orthogonal polarizations, which ensures stable operation. It was fabricated with a low-cost, printed-circuit-board and pick-and-place process. The performance of the metasurface was measured and its stability confirmed. The desired effects of amplification, polarization conversion, polarization selectivity, and nonreciprocal behavior were successfully demonstrated in both full-wave simulations and measurements. Due to its extremely small thickness (0.66 mm or 0.02λ at 10 GHz), the metasurface shows excellent performance for a wide range of incident angles, which exceeds ±30∘. It achieves a perfect (100%) polarization conversion ratio in simulation, and 98.4% in measurement.

关键词： Metamaterials Polarization

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Measuring success for a future vision: Defining impact in science gateways/virtual research environments

Measuring success for a future vision: Defining impact in sc...

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作者： Calyam, Prasad Wilkins-Diehr, Nancy Miller, Mark Brookes, Emre H. Arora, Ritu Chourasia, Amit Jennewein, Douglas M. Nandigam, Viswanath Drew LaMar, M. Cleveland, Sean B. Newman, Greg Wang, Shaowen Zaslavsky, Ilya Cianfrocco, Michael A. Ellett, Kevin Tarboton, David Jeffery, Keith G. Zhao, Zhiming González-Aranda, Juan Perri, Mark J. Tucker, Greg Candela, Leonardo Kiss, Tamas Gesing, Sandra Department of Electrical Engineering and Computer Science University of Missouri ColumbiaMO United States San Diego Supercomputer Center University of California San DiegoCA United States Department of Biochemistry University of Texas Health Science Center HoustonTX United States Texas Advanced Computing Center University of Texas at Austin AustinTX United States Information Technology Services University of South Dakota VermillionSD United States Biology Department College of William and Mary WilliamsburgVA United States Information Technology Services–Cyberinfrastructure University of Hawaii HonoluluHI United States Natural Resource Ecology Laboratory Colorado State University Fort CollinsCO United States Department of Geography and Geographic Information Science University of Illinois UrbanaIL United States Department of Biological Chemistry and Life Sciences Institute University of Michigan Ann ArborMI United States Pervasive Technology Institute Indiana University BloomingtonIN United States Civil and Environmental Engineering Utah State University LoganUT United States Keith G. Jeffery Consultants Faringdon United Kingdom Multiscale Networked Systems Group University of Amsterdam Amsterdam Netherlands Chief Technology Office LifeWatch ERIC Seville Spain Chemistry Department Sonoma State University Rohnert ParkCA United States Department of Geological Sciences CIRES University of Colorado Boulder BoulderCO United States National Research Council of Italy Pisa Italy Research Center for Parallel Computing University of Westminster London United Kingdom Center for Research Computing University of Notre Dame Notre DameIN United States

Scholars worldwide leverage science gateways/virtual research environments (VREs) for a wide variety of research and education endeavors spanning diverse scientific fields. Evaluating the value of a given science gateway/VRE to its constituent community is critical in obtaining the financial and human resources necessary to sustain operations and increase adoption in the user community. In this article, we feature a variety of exemplar science gateways/VREs and detail how they define impact in terms of, for example, their purpose, operation principles, and size of user base. Further, the exemplars recognize that their science gateways/VREs will continuously evolve with technological advancements and standards in cloud computing platforms, web service architectures, data management tools and cybersecurity. Correspondingly, we present a number of technology advances that could be incorporated in next-generation science gateways/VREs to enhance their scope and scale of their operations for greater success/impact. The exemplars are selected from owners of science gateways in the science Gateways Community Institute (SGCI) clientele in the United States, and from the owners of VREs in the International Virtual Research Environment Interest Group (VRE-IG) of the Research Data Alliance. Thus, community-driven best practices and technology advances are compiled from diverse expert groups with an international perspective to envisage futuristic science gateway/VRE innovations. © 2020 John Wiley & Sons, Ltd.

关键词： Web services

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Leveraging randomized compiling for the quantum imaginary-time-evolution algorithm

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Physical Review Research 2022年第3期4卷 033140-033140页

作者： Jean-Loup Ville Alexis Morvan Akel Hashim Ravi K. Naik Marie Lu Bradley Mitchell John-Mark Kreikebaum Kevin P. O'Brien Joel J. Wallman Ian Hincks Joseph Emerson Ethan Smith Ed Younis Costin Iancu David I. Santiago Irfan Siddiqi Quantum Nanoelectronics Laboratory Dept. of Physics University of California at Berkeley Berkeley California 94720 USA Computational Research Division Lawrence Berkeley National Lab Berkeley California 94720 USA Materials Sciences Division Lawrence Berkeley National Lab Berkeley California 94720 USA Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA Inst. for Quantum Computing and Dept. of Applied Mathematics University of Waterloo Waterloo Ontario Canada N2L 3G1 Quantum Benchmark Inc. Kitchener Ontario Canada N2H 5G5

Recent progress in noisy intermediate-scale quantum (NISQ) hardware shows that quantum devices may be able to tackle complex problems even without error correction. However, coherent errors due to the increased complexity of these devices is an outstanding issue. They can accumulate through a circuit, making their impact on algorithms hard to predict and mitigate. Iterative algorithms like quantum imaginary time evolution are susceptible to these errors. This article presents the combination of both noise tailoring using randomized compiling and error mitigation with purification. We also show that cycle benchmarking gives an estimate of the reliability of the purification. We apply this method to the quantum imaginary time evolution of a transverse field Ising model and report an energy estimation error and a ground-state infidelity both below 1%. Our methodology is general and can be used for other algorithms and platforms. We show how combining noise tailoring and error mitigation will push forward the performance of NISQ devices.

关键词： Measurement-based quantum computing Quantum algorithms Quantum benchmarking Quantum computation Quantum control Quantum information processing Quantum simulation

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