計算機視覺/圖像處理學術速遞[12.14]

2021-02-07 arXiv每日學術速遞

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cs.CV 方向,今日共計66篇

【1】 Entropy Maximization and Meta Classification for Out-Of-Distribution  Detection in Semantic Segmentation作者:Robin Chan,Matthias Rottmann,Hanno Gottschalk
機構:University of Wuppertal, Germany
連結:https://arxiv.org/abs/2012.06575【2】 Exploring Facial Expressions and Affective Domains for Parkinson  Detection作者:Luis Felipe Gomez-Gomez,Aythami Morales,Julian Fierrez,Juan Rafael Orozco-Arroyave
連結:https://arxiv.org/abs/2012.06563【3】 Detection of Binary Square Fiducial Markers Using an Event Camera作者:Hamid Sarmadi,Rafael Muñoz-Salinas,Miguel A. Olivares-Mendez,Rafael Medina-Carnicer
機構:Medina-Carnicer, University of Cordoba, Spain, The Maimonides Biomedical Research Institute of Cordoba (IMIBIC), Spain, Space Robotics Research Group, Interdisciplinary Centre for Security, Reliability and Trust (SnT), Universite du luxembourg, Luxembourg
連結:https://arxiv.org/abs/2012.06516【4】 Objectness-Guided Open Set Visual Search and Closed Set Detection作者:Nathan Drenkow,Philippe Burlina,Neil Fendley,Kachi Odoemene,Jared Markowitz
機構:The Johns Hopkins University Applied Physics Laboratory
連結:https://arxiv.org/abs/2012.06509【5】 Random Projections for Adversarial Attack Detection作者:Nathan Drenkow,Neil Fendley,Philippe Burlina
機構:The Johns Hopkins University Applied Physics Laboratory, Laurel, MD , USA
連結:https://arxiv.org/abs/2012.06405【6】 Classifying Breast Histopathology Images with a Ductal Instance-Oriented  Pipeline作者:Beibin Li,Ezgi Mercan,Sachin Mehta,Stevan Knezevich,Corey W. Arnold,Donald L. Weaver,Joann G. Elmore,Linda G. Shapiro
機構:University of Washington, Seattle, WA fUniversity of California, Los Angles, CA, Seattle Children's Hospital, Seattle, WA SUniversity of Vermont, Burlington, VT, Pathology Associates, Clovis,ca
備註:ICPR 2020. Submitted July 15th, 2020連結:https://arxiv.org/abs/2012.06136【7】 Color-related Local Binary Pattern: A Learned Local Descriptor for Color  Image Recognition標題:顏色相關局部二值模式:一種用於彩色圖像識別的學習型局部描述子作者:Bin Xiao,Tao Geng,Xiuli Bi,Weisheng Li
連結:https://arxiv.org/abs/2012.06132【8】 Spatio-attentive Graphs for Human-Object Interaction Detection作者:Frederic Z. Zhang,Dylan Campbell,Stephen Gould
機構:Australian National University
連結:https://arxiv.org/abs/2012.06060【9】 Uncertainty-Aware Deep Calibrated Salient Object Detection作者:Jing Zhang,Yuchao Dai,Xin Yu,Mehrtash Harandi,Nick Barnes,Richard Hartley
機構: Richard H,  Data, ReLER, University of Technology Sydney , Monash University
連結:https://arxiv.org/abs/2012.06020【10】 A Generative Approach for Detection-driven Underwater Image Enhancement作者:Chelsey Edge,Md Jahidul Islam,Christopher Morse,Junaed Sattar
備註:Under review for ICRA 2021連結:https://arxiv.org/abs/2012.05990【11】 Super-resolution Guided Pore Detection for Fingerprint Recognition作者:Syeda Nyma Ferdous,Ali Dabouei,Jeremy Dawson,Nasser M Nasrabadi
機構:West Virginia University, USA
連結:https://arxiv.org/abs/2012.05959【12】 Analyzing and Improving Generative Adversarial Training for Generative  Modeling and Out-of-Distribution Detection標題:面向產生式建模和離線檢測的產生式對抗性訓練分析與改進作者:Xuwang Yin,Shiying Li,Gustavo K. Rohde
機構:University of Virginia, Charlottesville, VA , USA
連結:https://arxiv.org/abs/2012.06568【13】 Automatic Test Suite Generation for Key-points Detection DNNs Using  Many-Objective Search標題:基於多目標搜索的關鍵點檢測DNNs測試集自動生成作者:Fitash Ul Haq,Donghwan Shin,Lionel C. Briand,Thomas Stifter,Jun Wang
機構:University of Luxembourg, University of Ottawa, Ottawa, Canada, IEE S.A., Post Luxembourg
連結:https://arxiv.org/abs/2012.06511【14】 Artificial Intelligence for COVID-19 Detection -- A state-of-the-art  review作者:Parsa Sarosh,Shabir A. Parah,Romany F Mansur,G. M. Bhat
機構:India-, New Valley University, El-Kharja, Egypt, Institute of Technology, University of Kashmir, JK
連結:https://arxiv.org/abs/2012.06310【1】 A new automatic approach to seed image analysis: From acquisition to  segmentation作者:A. M. P. G. Vale,M. Ucchesu,C. Di Ruberto,A. Loddo,J. M. Soares,G. Bacchetta
連結:https://arxiv.org/abs/2012.06414【2】 Few-Shot Segmentation Without Meta-Learning: A Good Transductive  Inference Is All You Need?標題:沒有元學習的Few-Shot分割:一個好的歸納推理就是你所需要的全部嗎?作者:Malik Boudiaf,Hoel Kervadec,Ziko Imtiaz Masud,Pablo Piantanida,Ismail Ben Ayed,Jose Dolz
機構:Pablo piantanida, ETS Montreal ETS Montreal, CentraleSupelec-CNRS, Universite Paris-Saclay
備註:12 pages, 3 figures, 9 tables. Code available at this https URL連結:https://arxiv.org/abs/2012.06166【3】 Superpixel Segmentation Based on Spatially Constrained Subspace  Clustering作者:Hua Li,Yuheng Jia,Runmin Cong,Wenhui Wu,Sam Kwong,Chuanbo Chen
備註:Accepted by IEEE Transactions on Industrial Informatics, 2020連結:https://arxiv.org/abs/2012.06149【4】 Uncertainty-driven refinement of tumor-core segmentation using 3D-to-2D  networks with label uncertainty標題:基於標籤不確定的3D-to-2D網絡的不確定性驅動的腫瘤核心分割精化作者:Richard McKinley,Micheal Rebsamen,Katrin Daetwyler,Raphael Meier,Piotr Radojewski,Roland Wiest
機構:Support Centre for Advanced Neuroimaging University Institute of Diagnostic and, Interventional Neuroradiology, Inselspital, Bern University Hospital, Bern, Switzerland
備註:Presented (virtually) in the MICCAI Brainles workshop 2020. Accepted for publication in Brainles proceedings連結:https://arxiv.org/abs/2012.06436【1】 Iso-Points: Optimizing Neural Implicit Surfaces with Hybrid  Representations作者:Wang Yifan,Shihao Wu,Cengiz Oztireli,Olga Sorkine-Hornung
機構:IETH Zurich ,University of Cambridge
連結:https://arxiv.org/abs/2012.06434【1】 Writer Identification and Writer Retrieval Based on NetVLAD with  Re-ranking作者:Shervin Rasoulzadeh,Bagher Babaali
機構:Statistics and Computer Science, College of Science, University of Tehran,Tehran, Iran
備註:This paper is a preprint of a paper submitted to IET Biometrics. If accepted, the copy of record will be available at the IET Digital Library連結:https://arxiv.org/abs/2012.06186【1】 A Comprehensive Study of Deep Video Action Recognition作者:Yi Zhu,Xinyu Li,Chunhui Liu,Mohammadreza Zolfaghari,Yuanjun Xiong,Chongruo Wu,Zhi Zhang,Joseph Tighe,R. Manmatha,Mu Li
備註:Technical report. Code and model zoo can be found at this https URL連結:https://arxiv.org/abs/2012.06567【2】 Spatial Temporal Transformer Network for Skeleton-based Action  Recognition作者:Chiara Plizzari,Marco Cannici,Matteo Matteucci
機構:Politecnico di Milano, Milano, Italy
備註:Accepted as ICPRW2020 (FBE2020, Workshop on Facial and Body Expressions, micro-expressions and behavior recognition) 8 pages, 2 figures. arXiv admin note: substantial text overlap with arXiv:2008.07404連結:https://arxiv.org/abs/2012.06399【1】 Unsupervised deep learning for individualized brain functional network  identification機構:Center for Biomedical Image Computing and Analytics(CBICA), University of Pennsylvania, Philadelphia, PA, USA
連結:https://arxiv.org/abs/2012.06494【2】 Relighting Images in the Wild with a Self-Supervised Siamese  Auto-Encoder作者:Yang Liu,Alexandros Neophytou,Sunando Sengupta,Eric Sommerlade
機構:University of Surrey, UK, Microsoft Corporation, Reading, UK, Alexandros. Neophytou, Sunando. Sengupta
連結:https://arxiv.org/abs/2012.06444【3】 D2-Net: Weakly-Supervised Action Localization via Discriminative  Embeddings and Denoised Activations標題:D2-網:基於判別嵌入和去噪激活的弱監督動作定位作者:Sanath Narayan,Hisham Cholakkal,Munawar Hayat,Fahad Shahbaz Khan,Ming-Hsuan Yang,Ling Shao
機構:Inception Institute of Artificial Intelligence, UAE ,Mohamed bin Zayed University of AI, UAE, Monash University, Australia ,University of California, Merced, USA ,Google Research
連結:https://arxiv.org/abs/2012.06440【4】 Context Matters: Graph-based Self-supervised Representation Learning for  Medical Images作者:Li Sun,Ke Yu,Kayhan Batmanghelich
機構:University of Pittsburgh, USA
連結:https://arxiv.org/abs/2012.06457【1】 Learning Omni-frequency Region-adaptive Representations for Real Image  Super-Resolution作者:Xin Li,Xin Jin,Tao Yu,Yingxue Pang,Simeng Sun,Zhizheng Zhang,Zhibo Chen
機構:CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System, University of Science and Technology of China, Hefei , China
連結:https://arxiv.org/abs/2012.06131【1】 A MAC-less Neural Inference Processor Supporting Compressed, Variable  Precision Weights標題:一種支持壓縮變精度權值的無MAC神經推理處理器連結:https://arxiv.org/abs/2012.06018【2】 Parallelized Rate-Distortion Optimized Quantization Using Deep Learning作者:Dana Kianfar,Auke Wiggers,Amir Said,Reza Pourreza,Taco Cohen
機構:th Reza pourreza, Qualcomm AI Research, Qualcomm Al Research
備註:6 pages; To be published at IEEE MMSP 2020 Proceedings連結:https://arxiv.org/abs/2012.06380【1】 Detailed 3D Human Body Reconstruction from Multi-view Images Combining  Voxel Super-Resolution and Learned Implicit Representation標題:體素超解析度和學習隱式表示相結合的多視角圖像細節三維人體重建作者:Zhongguo Li,Magnus Oskarsson,Anders Heyden
機構:Received: date Accepted: date
連結:https://arxiv.org/abs/2012.06178【1】 EventHands: Real-Time Neural 3D Hand Reconstruction from an Event Stream標題:EventHands:基於事件流的實時神經3D手部重建作者:Viktor Rudnev,Vladislav Golyanik,Jiayi Wang,Hans-Peter Seidel,Franziska Mueller,Mohamed Elgharib,Christian Theobalt
機構:Max Planck Institute for Informatics, Saarland Informatics Campus, DAVIS,C, Event Camera
連結:https://arxiv.org/abs/2012.06475【2】 A Log-likelihood Regularized KL Divergence for Video Prediction with A  3D Convolutional Variational Recurrent Network標題:三維卷積變分遞歸網絡視頻預測的對數似然正則化KL散度作者:Haziq Razali,Basura Fernando
連結:https://arxiv.org/abs/2012.06123【3】 A novel joint points and silhouette-based method to estimate 3D human  pose and shape標題:一種新的基於關節點和輪廓的三維人體姿態和形狀估計方法作者:Zhongguo Li,Anders Heyden,Magnus Oskarsson
機構:Lund University, Lund, Sweden
備註:Accepted to ICPR 2020 3DHU workshop連結:https://arxiv.org/abs/2012.06109【4】 3D Scattering Tomography by Deep Learning with Architecture Tailored to  Cloud Fields作者:Yael Sde-Chen,Yoav Y. Schechner,Vadim Holodovsky,Eshkol Eytan
機構:Technion-Israel Institute of Technology, Haifa, Israel, The Weizmann Institute of Science, Rehovot, Israel
連結:https://arxiv.org/abs/2012.05960【1】 Video Camera Identification from Sensor Pattern Noise with a Constrained  ConvNet標題:基於約束凸網的攝像機從傳感器模式噪聲中的識別作者:Derrick Timmerman,Swaroop Bennabhaktula,Enrique Alegre,George Azzopardi
機構:Azzopardiliod, Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence, University of Groningen, The Netherlands,  Group for Vision and Intelligent Systems, Universidad de Leon, spain, Keywords: Source Camera Identification Video Device Identification, Video Forensics, Sensor Pattern Noise
備註:Paper Accepted in - 10th International Conference on Pattern Recognition Applications and Methods (ICPRAM 2021)連結:https://arxiv.org/abs/2012.06277【2】 Intrinsic Temporal Regularization for High-resolution Human Video  Synthesis作者:Lingbo Yang,Zhanning Gao,Peiran Ren,Siwei Ma,Wen Gao
機構:. Institute of Digital Media, Peking University, . Alibaba DAMO Academy, Driving, Frames, Source, Images
備註:10 pages, work done during internship at Alibaba DAMO Academy連結:https://arxiv.org/abs/2012.06134【3】 Learning Order Parameters from Videos of Dynamical Phases for Skyrmions  with Neural Networks標題:用神經網絡從天空微子的動力學相視頻中學習序參數作者:Weidi Wang,Zeyuan Wang,Yinghui Zhang,Bo Sun,Ke Xia
機構:The Center for Advanced Quantum Studies, Beijing Normal University, Beijing , China, Drexel University, Philadelphia, PA , USA, College of Education for the Future, Beijing Normal University, Beijing , China, Beijing Computational Science Research Center, Beijing , China, (Dated: December ,)
連結:https://arxiv.org/abs/2012.06308【1】 LayoutGMN: Neural Graph Matching for Structural Layout Similarity標題:LayoutGMN:面向結構布局相似度的神經網絡圖匹配作者:Akshay Gadi Patil,Manyi Li,Matthew Fisher,Manolis Savva,Hao Zhang
機構: Simon Fraser University ,Adobe Research
連結:https://arxiv.org/abs/2012.06547【2】 Dependency Decomposition and a Reject Option for Explainable Models作者:Jan Kronenberger,Anselm Haselhoff
機構:Computer Science Institute, Ruhr West University of Applied Sciences Ruhr West University of Applied Sciences
備註:Accepted at CVPR 2019 Workshop "DThree19: Dependable Deep Detectors"連結:https://arxiv.org/abs/2012.06523【3】 Confidence Estimation via Auxiliary Models作者:Charles Corbière,Nicolas Thome,Antoine Saporta,Tuan-Hung Vu,Matthieu Cord,Patrick Pérez
連結:https://arxiv.org/abs/2012.06508【4】 DeepObjStyle: Deep Object-based Photo Style Transfer標題:DeepObjStyle:基於深度對象的照片樣式轉換作者:Indra Deep Mastan,Shanmuganathan Raman
機構:Indian Institute of Technology Gandhinagar, Gandhinagar, Gujarat, India
連結:https://arxiv.org/abs/2012.06498【5】 DILIE: Deep Internal Learning for Image Enhancement作者:Indra Deep Mastan,Shanmuganathan Raman
機構:Indian Institute of Technology Gandhinagar, Gandhinagar, Gujarat, India
連結:https://arxiv.org/abs/2012.06469【6】 Cyclic orthogonal convolutions for long-range integration of features作者:Federica Freddi,Jezabel R Garcia,Michael Bromberg,Sepehr Jalali,Da-Shan Shiu,Alvin Chua,Alberto Bernacchia
機構:MediaTek Research, December
連結:https://arxiv.org/abs/2012.06462【7】 Imitation-Based Active Camera Control with Deep Convolutional Neural  Network機構:KIOS Research and Innovation Center of Excellence, University of Cyprus, Panepistimiou Avenue, Nicosia Cyprus, December
備註:Paper accepted in Fourth IEEE International Conference on Image Processing, Applications, and Systems (IEEE IPAS 2020)連結:https://arxiv.org/abs/2012.06428【8】 A Multi-task Joint Framework for Real-time Person Search作者:Ye Li,Kangning Yin,Jie Liang,Chunyu Wang,Guangqiang Yin
機構:Received: date Accepted:date
連結:https://arxiv.org/abs/2012.06418【9】 Cyclopean Geometry of Binocular Vision作者:Miles Hansard,Radu Horaud
機構:INRIA Rhone-Alpes-, Avenue de lEurope',  Montbonnot, France.
連結:https://arxiv.org/abs/2012.06363【10】 Self-Growing Spatial Graph Network for Context-Aware Pedestrian  Trajectory Prediction標題:基於自生長空間圖網絡的上下文感知行人軌跡預測作者:Sirin Haddad,Siew-Kei Lam
機構:Received: dateAccepted: date
連結:https://arxiv.org/abs/2012.06320【11】 One Point is All You Need: Directional Attention Point for Feature  Learning作者:Liqiang Lin,Pengdi Huang,Chi-Wing Fu,Kai Xu,Hao Zhang,Hui Huang
機構:Shenzhen University, The Chinese University of Hong Kong, National University of Defense Technology, Simon Fraser University
連結:https://arxiv.org/abs/2012.06257【12】 Garment Recommendation with Memory Augmented Neural Networks作者:Lavinia De Divitiis,Federico Becattini,Claudio Baecchi,Alberto Del Bimbo
機構:Bimb,-,-,-, University of Florence, Italy
連結:https://arxiv.org/abs/2012.06200【13】 Learning Edge-Preserved Image Stitching from Large-Baseline Deep  Homography作者:Lang Nie,Chunyu Lin,Kang Liao,Yao Zhao
連結:https://arxiv.org/abs/2012.06194【14】 AViNet: Diving Deep into Audio-Visual Saliency Prediction作者:Samyak Jain,Pradeep Yarlagadda,Ramanathan Subramanian,Vineet Gandhi
機構:CVIT, Kohli Centre on Intelligent Systems, IIIT Hyderabad ,IIT Ropar
連結:https://arxiv.org/abs/2012.06170【15】 A Dark Flash Normal Camera作者:Zhihao Xia,Jason Lawrence,Supreeth Achar
機構: Washington University in St. Louis ,Google Research
連結:https://arxiv.org/abs/2012.06125【16】 How to Train PointGoal Navigation Agents on a (Sample and Compute)  Budget作者:Erik Wijmans,Irfan Essa,Dhruv Batra
機構: Georgia Institute of Technology,Facebook, AI Research, Google Research Atlanta
連結:https://arxiv.org/abs/2012.06117【17】 Monocular Real-time Full Body Capture with Inter-part Correlations作者:Yuxiao Zhou,Marc Habermann,Ikhsanul Habibie,Ayush Tewari,Christian Theobalt,Feng Xu
機構:Tsinghua University ,Max Planck Institute for Informatics ,Saarland Informatics Campus
連結:https://arxiv.org/abs/2012.06087【18】 Mesoscopic photogrammetry with an unstabilized phone camera作者:Kevin C. Zhou,Colin Cooke,Jaehee Park,Ruobing Qian,Roarke Horstmeyer,Joseph A. Izatt,Sina Farsiu
機構:Duke University, Durham, NC
連結:https://arxiv.org/abs/2012.06044【19】 Vision-based Price Suggestion for Online Second-hand Items作者:Liang Han,Zhaozheng Yin,Zhurong Xia,Li Guo,Mingqian Tang,Rong Jin
機構:Stony Brook University, Alibaba Group, Alibaba group
連結:https://arxiv.org/abs/2012.06009【20】 Image-Graph-Image Translation via Auto-Encoding作者:Chenyang Lu,Gijs Dubbelman
機構:Eindhoven University of Technology, Eindhoven, The Netherlands
連結:https://arxiv.org/abs/2012.05975【21】 Risk & returns around FOMC press conferences: a novel perspective from  computer vision標題:FOMC新聞發布會前後的風險與收益:計算機視覺的新視角連結:https://arxiv.org/abs/2012.06573【22】 AIforCOVID: predicting the clinical outcomes in patients with COVID-19  applying AI to chest-X-rays. An Italian multicentre study標題:AIforCOVID:將人工智慧應用於胸部X光片,預測冠狀病毒患者的臨床結果。一項義大利多中心研究作者:Paolo Soda,Natascha Claudia D'Amico,Jacopo Tessadori,Giovanni Valbusa,Valerio Guarrasi,Chandra Bortolotto,Muhammad Usman Akbar,Rosa Sicilia,Ermanno Cordelli,Deborah Fazzini,Michaela Cellina,Giancarlo Oliva,Giovanni Callea,Silvia Panella,Maurizio Cariati,Diletta Cozzi,Vittorio Miele,Elvira Stellato,Gian Paolo Carrafiello,Giulia Castorani,Annalisa Simeone,Lorenzo Preda,Giulio Iannello,Alessio Del Bue,Fabio Tedoldi,Marco Alì,Diego Sona,Sergio Papa
機構:Unit of Computer Systems and Bioinformatics, University Campus Bio-Medico of Rome, Via Alvaro del Portillo , Rome, Italy, Centro Diagnostico Italiano S.p.A., Via S. Saint Bon, Pattern Analysis and Computer Vision, Istituto Italiano di Tecnologia, Via Morego , Genoa, Italy, Co ,Bracco Imaging S.p.A., Via Caduti di Marcinelle , Milan, Italy, Control, and Management Engineering, Sapienza University of Rome, Via Ariosto, Radiology Institute, Fondazione IRCCS Policlinico San Matteo, Viale Golgi , Pavia, Italy, Electrical, Electronic and Telecommunications Engineering-University of Genova, Via, All'Opera Pia , A, Genoa, Italy, ASST Fatebenefratelli Sacco Piazza Principessa Clotilde , Milan, Italy, Diagnostic and interventional radiology unit, ASST Santi Paolo e Carlo-San Paolo Hospital, Via Antonio di Rudini , Diagnostic and Radiology Units, ASST Santi Paolo, e Carlo-San Paolo Hospital, Via Antonio di Rudini , Milan, Italy, Careggi University Hospital, Largo Piero Palagi , Florence, Italy
連結:https://arxiv.org/abs/2012.06531【23】 RENATA: REpreseNtation And Training Alteration for Bias Mitigation作者:William Paul,Armin Hadzic,Neil Joshi,Phil Burlina
機構:Enforcing fairness, domain adaption in [,] uses this strategy. [,], REpreseNtation And Training Alteration for Bias Mitigation. Preprint , (December ,), pages., uses a separate adversarial network in a natural language processing, task to predict the protected factor, and modifies the word embed-, dings to reduce the adversary's performance. Concurrent studies
連結:https://arxiv.org/abs/2012.06387【24】 Feature Selection Based on Sparse Neural Network Layer with Normalizing  Constraints作者:Peter Bugata,Peter Drotar
備註:This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible連結:https://arxiv.org/abs/2012.06365【25】 Privacy-preserving medical image analysis作者:Alexander Ziller,Jonathan Passerat-Palmbach,Théo Ryffel,Dmitrii Usynin,Andrew Trask,Ionésio Da Lima Costa Junior,Jason Mancuso,Marcus Makowski,Daniel Rueckert,Rickmer Braren,Georgios Kaissis
機構:Institute of Diagnostic, and Interventional Radiolog, Institute for Artificial Intelligence, and Informatics in Medicine, Technical University of Munich, Munich, Gerr, ermany, Theo Ryffel, Arkhn, Imperial College London, INRIA, ENS, PSL University, London, United Kingdom, Paris,France, j. passerat-palmbachimperial. ac.uk, University of Oxford, Oxford, United Kingdom, dmitrii. usynin,imperial.ac.uk, Ionesio Da Lima Costa Junior, Universidade Federal de Campina Grande, Cape Privacy, Campina Grande, Paraiba, Brazil, New York, United States of America, Daniel Bueckert
備註:Accepted at the workshop for Medical Imaging meets NeurIPS, 34th Conference on Neural Information Processing Systems (NeurIPS) December 11, 2020連結:https://arxiv.org/abs/2012.06354【26】 State-of-the-art Machine Learning MRI Reconstruction in 2020: Results of  the Second fastMRI Challenge標題:2020年最新的機器學習MRI重建:第二屆FAST MRI挑戰賽的結果作者:Matthew J. Muckley,Bruno Riemenschneider,Alireza Radmanesh,Sunwoo Kim,Geunu Jeong,Jingyu Ko,Yohan Jun,Hyungseob Shin,Dosik Hwang,Mahmoud Mostapha,Simon Arberet,Dominik Nickel,Zaccharie Ramzi,Philippe Ciuciu,Jean-Luc Starck,Jonas Teuwen,Dimitrios Karkalousos,Chaoping Zhang,Anuroop Sriram,Zhengnan Huang,Nafissa Yakubova,Yvonne Lui,Florian Knoll
機構:Facebook AI Research, New York, NY, USA, AIRS Medical, Seoul, South Korea,  Yonsei University, Seoul, Korea, Siemens Healthineers, Princeton, NJ, USA, Siemens Healthcare GmbH, Erlangen, Germany, CEA (NeuroSpin) Inria Saclay (Parietal), Universite Paris-Saclay, F-, Gif-sur-Yvette, France, Departement d'Astrophysique, CEA-Saclay, Gif-sur-Yvette, France, Radboud University Medical Center, Nijmegen, Netherlands,  Amsterdam UMC, Amsterdam, Netherlands, Facebook AI Research, Menlo Park, CA, USA, Equal contribution., December
備註:16 pages, 7 figures, 3 tables連結:https://arxiv.org/abs/2012.06318【27】 Deep-Learning-Based Kinematic Reconstruction for DUNE作者:Junze Liu,Jordan Ott,Julian Collado,Benjamin Jargowsky,Wenjie Wu,Jianming Bian,Pierre Baldi
機構:(For the DUNE Collaboration), University of California, Irvine, Irvine, CA , pfbaldicics. uci. edu
連結:https://arxiv.org/abs/2012.06181【28】 DSRNA: Differentiable Search of Robust Neural Architectures作者:Ramtin Hosseini,Xingyi Yang,Pengtao Xie
機構:UC San Diego,  Gilman Dr, La Jolla, CA , Gilman Dr, La Jolla, CA
連結:https://arxiv.org/abs/2012.06122【29】 Provable Defense against Privacy Leakage in Federated Learning from  Representation Perspective作者:Jingwei Sun,Ang Li,Binghui Wang,Huanrui Yang,Hai Li,Yiran Chen
機構:Duke University, December
連結:https://arxiv.org/abs/2012.06043機器翻譯,僅供參考
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  • 計算機視覺/圖像處理學術速遞[02.03]
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    Sparse Semantic Scene Completion Network for LiDAR Point Clouds標題:S3CNet:一種面向LiDAR點雲的稀疏語義場景補全網絡作者:Ran Cheng,Christopher Agia,Yuan Ren,Xinhai Li,Liu Bingbing備註:14
  • 計算機視覺/圖像處理學術速遞[08.03]
    //arxiv.org/abs/2007.15818【4】 Weakly supervised one-stage vision and language disease detection using large scale pneumonia and pneumothorax studies標題:使用大規模肺炎和氣胸研究的弱監督一期視覺和語言疾病檢測
  • 計算機視覺/圖像處理學術速遞[10.08]
    Yap, Eibe Frank 連結:https://arxiv.org/abs/2010.03341【3】 Multi-label classification of promotions in digital leaflets using textual and visual information標題:使用文本和視覺信息對數字傳單中的促銷進行多標籤分類
  • 計算機視覺/圖像處理學術速遞[11.03]
    Huisman 備註:Accepted to Medical Imaging Meets NeurIPS Workshop of the 34th Conference on Neural Information Processing Systems (NeurIPS 2020)連結:https://arxiv.org/abs/2011.00263【12
  • 計算機視覺/圖像處理學術速遞[08.20]
    】 TIDE: A General Toolbox for Identifying Object Detection Errors作者: Daniel Bolya, Judy Hoffman 備註:ECCV 2020 Spotlight Paper連結:https://arxiv.org/abs/2008.08115【12
  • 計算機視覺將用來處理相機圖像
    得到一些數據以及判斷,然後推斷應該怎麼工作,這其中包括對人的數據進行分析,包括性別,年齡,籍貫等等,也包括對機器的運算發送指令給人工,使用代碼來進行循環.然後在人工智慧的背後,一個重要的單位就是計算機視覺,它們主要負責識別,分類,檢測,填充,分割.首先計算機視覺可以幫助我們更好的了解自己的眼睛,也就是我們的眼睛,視覺的作用在於生物可以更好的了解周圍的世界。
  • 計算機視覺和圖像處理之間有什麼區別?
    現代機器視覺系統背後的的核心動機在於模擬人類視覺,用於識別圖案,面部以及將將2D圖像轉化為3D模型等。在概念層面,圖像處理和計算機視覺之間存在很多重疊,並且經常被誤解的術語可以互換使用。在這裡,我們簡要概述了這些技術,並解釋了它們在基礎層面上的不同之處。
  • 計算機視覺/圖像處理學術速遞[08.06]
    2020連結:https://arxiv.org/abs/2008.01860【3】 Structure Preserving Stain Normalization of Histopathology Images Using Self-Supervised Semantic Guidance標題:基於自監督語義引導的組織病理圖像結構保持染色歸一化
  • 計算機視覺(圖像)技術:視覺圖像搜索綜述
    這些年計算機視覺識別和搜索這個領域非常熱鬧,後期出現了很多的創業公司,大公司也在這方面也花了很多力氣在做。做視覺搜索,其實是深度學習(或人工智慧)領域最重要的研究課題之一,在現實生活中有著非常廣泛的應用。  通常,視覺搜索包含了兩步任務:首先,待搜索物體的檢測與定位;其次,從庫(知識圖譜、圖片庫、信息庫等)中搜索該物體,或查詢相關聯的場景。
  • 【期刊速遞】高光譜遙感圖像處理與信息提取直播預告
    高光譜圖像處理與信息提取技術是高光譜遙感領域的核心研究內容之一。隨著智能化信息分析和高性能硬體處理技術的發展,高光譜遙感衛星系統也將步入智能化時代。如何利用人工智慧等最新成果,發展高光譜圖像處理與信息提取的高性能實時處理技術?如何發揮高光譜遙感的優勢和特點,發展新理論和新方法?
  • 包括的領域有計算機視覺,語音識別,自然語言處理,圖像識別等
    現在人工智慧已經包括的領域有計算機視覺,語音識別,自然語言處理,圖像識別等。人工智慧的步驟人工智慧基本步驟包括,信息提取->信息分析->假設建模->學習->泛化,具體步驟。如果說計算機視覺是讓計算機看到一張黑白的二維圖像,那麼它可以識別字符串,可以通過圖像獲取某個標註的信息,它具有特定的識別圖像,可以從圖像分析出某個基本的結構。
  • 機器視覺和智能圖像處理技術之間的關係
    一般認為機器視覺「是通過光學裝置和非接觸傳感器自動地接受和處理一個真實場景的圖像,通過分析圖像獲得所需信息或用於控制機器運動的裝置」,可以看出智能圖像處理技術在機器視覺中佔有舉足輕重的位置。 智能圖像處理是指一類基於計算機的自適應於各種應用場合的圖像處理和分析技術,本身是一個獨立的理論和技術領域,但同時又是機器視覺中的一項十分重要的技術支撐。
  • 智能圖像處理 讓機器視覺及其應用更智能高效
    編者按:無論是「中國製造2025」還是「工業4.0」都離不開人工智慧,離不開計算機視覺,而智能圖像處理是機器視覺的核心技術,隨著圖像處理水平的不斷提高,一定會有力地推動機器視覺的迅速發展。
  • 計算機視覺 vs 機器視覺
    計算機視覺和機器視覺通常被認為是同一個行業,其實它們是重疊技術的不同術語。計算機視覺廣義上是指圖像分析的捕獲和自動化,並著重於在廣泛的理論和實際應用中的圖像分析功能。傳統上,機器視覺是借鑑參考了計算機視覺技術,在某些工業或實際應用中根據視覺系統完成圖像分析的某些功能或結果。視覺系統使用軟體來識別預編程的功能,該系統可根據發現結果觸發各種設定的「動作」。例如,在食品和飲料行業的裝瓶廠中,視覺系統可用於識別多個物體。它可以驗證空瓶本身沒有損壞和異物。
  • 人工智慧與計算機視覺
    計算機視覺是使用計算機及相關設備對生物視覺的一種模擬,是人工智慧領域的一個重要部分,它的研究目標是使計算機具有通過二維圖像認知三維環境信息的能力。計算機視覺是以圖象處理技術、信號處理技術、概率統計分析、計算幾何、神經網絡、機器學習理論和計算機信息處理技術等為基礎,通過計算機分析與處理視覺信息。
  • 視覺感知-從人類視覺到計算機視覺
    1.4億個神經元組成,是大腦中最神秘的部分之一,負責處理和解釋視覺數據以提供感知力並建立記憶。例如給定一幅圖像,我們可以利用上下文和先驗知識得知整個故事。 但是,使計算機感知視覺世界有多困難?截至2019年,我們才取得了一定進展,但依舊還有很長的路要走。計算機視覺是計算機科學的一個相對較新的領域,大約有60年的歷史。
  • 計算機視覺領域的王者與榮耀丨CCF-GAIR 2018
    在這背後,安防視頻監控與醫療影像,也成為眾多AI從業者尤為青睞的兩大行業。當計算機視覺研究與落地大潮湧動之際,第三屆CCF-GAIR全球人工智慧與機器人峰會「計算機視覺專場」,眾多科技巨頭首席技術官、獨角獸首席科學家、國際學術頂會主席、世界名校AI實驗室主任將會公開分享最前沿的計算機視覺技術研究與商用成果。
  • 騰訊優圖學術再進階 論文入選計算機視覺領頂級會議CVPR 2018
    據外媒報導,即將在6月美國鹽湖城舉行的計算機視覺頂級會議CVPR 2018,騰訊優圖的其中兩篇入選論文,由於其較高的應用價值,受到學術界和產業界的關注。騰訊優圖論文再次入庫頂級學術會議作為計算機視覺領域最高級別的會議之一的CVPR,其論文集通常代表著計算機視覺領域最新的發展方向和水平。這也是騰訊優圖繼2017年在另一計算機視覺頂級會議ICCV會議中獲得12篇論文被收錄,包含3篇口頭報告(該類論文僅佔總投稿數2.1%)的成績後,2018年,科研成果再次豐收,論文被CVPR2018收錄。
  • 計算機視覺:圖像檢測和圖像分割有什麼區別?
    字幕組雙語原文:計算機視覺:圖像檢測和圖像分割有什麼區別?英語原文:What is the difference between Object Detection and Image Segmentation?翻譯:雷鋒字幕組(明明知道)人工智慧中的圖像處理人工智慧對於圖像處理有不同的任務。