David Crandall

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Chen YuProfessor, The University of Texas at AustinDirección de correo verificada de austin.utexas.edu
Apu KapadiaProfessor of Computer Science, Indiana University BloomingtonDirección de correo verificada de indiana.edu
Daniel HuttenlocherMassachusetts Institute of TechnologyDirección de correo verificada de mit.edu
Mingze XuAppleDirección de correo verificada de apple.com
Stefan LeeAssistant Professor, Oregon State UniversityDirección de correo verificada de oregonstate.edu
Geoffrey FoxProfessor of Computer Science, University of Virginia, Biocomplexity InstituteDirección de correo verificada de virginia.edu
Sven BambachData Science & Machine Learning at Nationwide Children's HospitalDirección de correo verificada de nationwidechildrens.org
Dhruv BatraGeorgia Tech | Prev: FAIR (Meta AI)Dirección de correo verificada de gatech.edu
Rob TemplemanExecutive Director for Cyber Innovation, Indiana UniversityDirección de correo verificada de iu.edu
Mohammed KorayemDirector of Data Science, Data Science R&D - CareerBuilderDirección de correo verificada de indiana.edu
John PadenAssoc. Scientist/Assoc. Director, University of KansasDirección de correo verificada de ku.edu
Wenguan WangZhejiang UniversityDirección de correo verificada de zju.edu.cn
Jiebo Luo, Fellow of NAI/ACM/AAAI/IE...Albert Arendt Hopeman Professor of Engineering, University of RochesterDirección de correo verificada de cs.rochester.edu
Md Alimoor RezaAssistant Professor, Drake UniversityDirección de correo verificada de drake.edu
Roberto HoyleAssistant Professor, Oberlin CollegeDirección de correo verificada de oberlin.edu
Michael CogswellSRI InternationalDirección de correo verificada de sri.com
Satoshi TsutsuiNanyang Technological UniversityDirección de correo verificada de indiana.edu
David LeakeProfessor of Computer Science, Indiana UniversityDirección de correo verificada de iu.edu
Selma ŠabanovićProfessor of Informatics, Indiana University BloomingtonDirección de correo verificada de iu.edu
Jon KleinbergProfessor of Computer Science, Cornell UniversityDirección de correo verificada de cs.cornell.edu

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David Crandall

Professor of Computer Science, Indiana University

Dirección de correo verificada de indiana.edu - Página principal

Computer vision machine learning data mining social networks


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
Mapping the world's photos DJ Crandall, L Backstrom, D Huttenlocher, J Kleinberg Proceedings of the 18th international conference on World wide web, 761-770, 2009	1126	2009
Ego4d: Around the world in 3,000 hours of egocentric video K Grauman, A Westbury, E Byrne, Z Chavis, A Furnari, R Girdhar, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022	883	2022
Feedback effects between similarity and social influence in online communities D Crandall, D Cosley, D Huttenlocher, J Kleinberg, S Suri Proceedings of the 14th ACM SIGKDD international conference on Knowledge …, 2008	883	2008
Inferring social ties from geographic coincidences DJ Crandall, L Backstrom, D Cosley, S Suri, D Huttenlocher, J Kleinberg Proceedings of the National Academy of Sciences 107 (52), 22436-22441, 2010	619	2010
Diverse beam search: Decoding diverse solutions from neural sequence models AK Vijayakumar, M Cogswell, RR Selvaraju, Q Sun, S Lee, D Crandall, ... arXiv preprint arXiv:1610.02424, 2016	581	2016
Lending a hand: Detecting hands and recognizing activities in complex egocentric interactions S Bambach, S Lee, DJ Crandall, C Yu Proceedings of the IEEE international conference on computer vision, 1949-1957, 2015	522	2015
Discrete-continuous optimization for large-scale structure from motion D Crandall, A Owens, N Snavely, D Huttenlocher CVPR 2011, 3001-3008, 2011	464	2011
Dynamic dual-attentive aggregation learning for visible-infrared person re-identification M Ye, J Shen, D J. Crandall, L Shao, J Luo Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020	433	2020
Spatial priors for part-based recognition using statistical models. D Crandall, P Felzenszwalb, D Huttenlocher IEEE Conference on Computer Vision and Pattern Recognition, 2005	433	2005
Landmark classification in large-scale image collections Y Li, DJ Crandall, DP Huttenlocher 2009 IEEE 12th international conference on computer vision, 1957-1964, 2009	380	2009
Discovering Localized Attributes for Fine-grained Recognition K Duan, D Parikh, D Crandall, K Grauman CVPR, 2012	359	2012
Why m heads are better than one: Training a diverse ensemble of deep networks S Lee, S Purushwalkam, M Cogswell, D Crandall, D Batra arXiv preprint arXiv:1511.06314, 2015	343	2015
Zero-shot video object segmentation via attentive graph neural networks W Wang, X Lu, J Shen, DJ Crandall, L Shao Proceedings of the IEEE/CVF international conference on computer vision …, 2019	323	2019
Weakly supervised learning of part-based spatial models for visual object recognition DJ Crandall, DP Huttenlocher Computer Vision–ECCV 2006: 9th European Conference on Computer Vision, Graz …, 2006	266	2006
Diverse beam search for improved description of complex scenes A Vijayakumar, M Cogswell, R Selvaraju, Q Sun, S Lee, D Crandall, ... Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018	257	2018
Privacy behaviors of lifeloggers using wearable cameras R Hoyle, R Templeman, S Armes, D Anthony, D Crandall, A Kapadia Proceedings of the 2014 ACM international joint conference on pervasive and …, 2014	243	2014
A survey on deep learning technique for video segmentation T Zhou, F Porikli, DJ Crandall, L Van Gool, W Wang IEEE transactions on pattern analysis and machine intelligence 45 (6), 7099-7122, 2022	240*	2022
Hope-net: A graph-based model for hand-object pose estimation B Doosti, S Naha, M Mirbagheri, DJ Crandall Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020	238	2020
Real-time, cloud-based object detection for unmanned aerial vehicles J Lee, J Wang, D Crandall, S Šabanović, G Fox 2017 First IEEE International Conference on Robotic Computing (IRC), 36-43, 2017	218	2017
Stochastic multiple choice learning for training diverse deep ensembles S Lee, S Purushwalkam Shiva Prakash, M Cogswell, V Ranjan, ... Advances in Neural Information Processing Systems 29, 2016	217	2016

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