David Crandall

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Chen YuProfessor, The University of Texas at AustinE-mail confirmado em austin.utexas.edu
Apu KapadiaProfessor of Computer Science, Indiana University BloomingtonE-mail confirmado em indiana.edu
Daniel HuttenlocherMassachusetts Institute of TechnologyE-mail confirmado em mit.edu
Mingze XuAppleE-mail confirmado em apple.com
Stefan LeeAssistant Professor, Oregon State UniversityE-mail confirmado em oregonstate.edu
Geoffrey FoxProfessor of Computer Science, University of Virginia, Biocomplexity InstituteE-mail confirmado em virginia.edu
Sven BambachData Science & Machine Learning at Nationwide Children's HospitalE-mail confirmado em nationwidechildrens.org
Dhruv BatraPrev: FAIR (Meta AI), Georgia TechE-mail confirmado em dhruvbatra.com
Rob TemplemanExecutive Director for Cyber Innovation, Indiana UniversityE-mail confirmado em iu.edu
Mohammed KorayemDirector of Data Science, Data Science R&D - CareerBuilderE-mail confirmado em indiana.edu
John PadenAssoc. Scientist/Assoc. Director, University of KansasE-mail confirmado em ku.edu
Md Alimoor RezaAssistant Professor, Drake UniversityE-mail confirmado em drake.edu
Jiebo Luo, Fellow of ACM/AAAI/IEEE/...Albert Arendt Hopeman Professor of Engineering, University of RochesterE-mail confirmado em cs.rochester.edu
Roberto HoyleAssistant Professor, Oberlin CollegeE-mail confirmado em oberlin.edu
Wenguan WangZhejiang UniversityE-mail confirmado em zju.edu.cn
Selma ŠabanovićProfessor of Informatics, Indiana University BloomingtonE-mail confirmado em iu.edu
Michael CogswellSRI InternationalE-mail confirmado em sri.com
Satoshi TsutsuiNanyang Technological UniversityE-mail confirmado em indiana.edu
David LeakeProfessor of Computer Science, Indiana UniversityE-mail confirmado em iu.edu
Jon KleinbergProfessor of Computer Science, Cornell UniversityE-mail confirmado em cs.cornell.edu

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David Crandall

Professor of Computer Science, Indiana University

E-mail confirmado em indiana.edu - Página inicial

Computer vision machine learning data mining social networks


Título Ordenar por citações Ordenar por ano Ordenar por título	Citado por Citado por	Ano
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	1130	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	1069	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	881	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	623	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	619	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	531	2015
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	492	2020
Discrete-continuous optimization for large-scale structure from motion D Crandall, A Owens, N Snavely, D Huttenlocher CVPR 2011, 3001-3008, 2011	464	2011
Spatial priors for part-based recognition using statistical models. D Crandall, P Felzenszwalb, D Huttenlocher IEEE Conference on Computer Vision and Pattern Recognition, 2005	437	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	376	2009
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	363	2015
Discovering Localized Attributes for Fine-grained Recognition K Duan, D Parikh, D Crandall, K Grauman CVPR, 2012	363	2012
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	343	2019
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	274*	2022
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	272	2018
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	267	2006
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	255	2020
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	249	2014
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	226	2017
Temporal recurrent networks for online action detection M Xu, M Gao, YT Chen, LS Davis, DJ Crandall Proceedings of the IEEE/CVF international conference on computer vision …, 2019	222	2019

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