Deva Ramanan

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James HaysGeorgia TechEmail yang diverifikasi di gatech.edu
Serge BelongieUniversity of CopenhagenEmail yang diverifikasi di di.ku.dk
Pietro PeronaCalifornia Institute of TechnologyEmail yang diverifikasi di caltech.edu
Michael MaireUniversity of ChicagoEmail yang diverifikasi di uchicago.edu
Tsung-Yi LinResearch Scientist, NVIDIAEmail yang diverifikasi di nvidia.com
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C. Lawrence ZitnickFAIR (Meta)Email yang diverifikasi di fb.com
Ross GirshickCo-Founder at VerceptEmail yang diverifikasi di vercept.com
David McAllesterProfessor, Toyota Technological Institute at ChicagoEmail yang diverifikasi di ttic.edu
Charless FowlkesDepartment of Computer Science, University of California, IrvineEmail yang diverifikasi di ics.uci.edu
Pedro FelzenszwalbBrown UniversityEmail yang diverifikasi di brown.edu
Yi YangResearch Scientist, Google DeepMindEmail yang diverifikasi di uci.edu
Peiyun HuApple IncEmail yang diverifikasi di apple.com
Gengshan YangWorld LabsEmail yang diverifikasi di worldlabs.ai
David ForsythProfessor of Computer Science, University of Illinois, Urbana ChampaignEmail yang diverifikasi di uiuc.edu
Hamed PirsiavashAssociate Professor at University of California, DavisEmail yang diverifikasi di ucdavis.edu
Yuxiong WangUniversity of Illinois Urbana-ChampaignEmail yang diverifikasi di illinois.edu
Simon LuceyDirector, Australian Institute for Machine Learning (AIML), University of AdelaideEmail yang diverifikasi di adelaide.edu
Achal DaveToyota Research InstituteEmail yang diverifikasi di tri.global
Shu KongTexas A&M UniversityEmail yang diverifikasi di tamu.edu

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Deva Ramanan

Professor, Robotics Institute, Carnegie Mellon University

Email yang diverifikasi di cs.cmu.edu - Beranda

Computer Vision Machine Learning


Judul Urutkan menurut kutipan Urutkan menurut tahun Urutkan menurut judul	Dikutip oleh Dikutip oleh	Tahun
Microsoft coco: Common objects in context TY Lin, M Maire, S Belongie, J Hays, P Perona, D Ramanan, P Dollár, ... Computer Vision–ECCV 2014: 13th European Conference, Zurich, Switzerland …, 2014	55226	2014
Object detection with discriminatively trained part-based models PF Felzenszwalb, RB Girshick, D McAllester, D Ramanan IEEE transactions on pattern analysis and machine intelligence 32 (9), 1627-1645, 2009	13379	2009
A discriminatively trained, multiscale, deformable part model P Felzenszwalb, D McAllester, D Ramanan 2008 IEEE conference on computer vision and pattern recognition, 1-8, 2008	4046	2008
Face detection, pose estimation, and landmark localization in the wild X Zhu, D Ramanan 2012 IEEE conference on computer vision and pattern recognition, 2879-2886, 2012	3122	2012
Articulated Human Detection with Flexible Mixtures-of-Parts Y Yang, D Ramanan Pattern Analysis and Machine Intelligence, IEEE Transactions on 35 (12 …, 2013	2559*	2013
Argoverse: 3d tracking and forecasting with rich maps MF Chang, J Lambert, P Sangkloy, J Singh, S Bak, A Hartnett, D Wang, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019	1600	2019
Microsoft coco: Common objects in context [C] TY Lin, M Maire, S Belongie, J Hays, P Perona, D Ramanan, P Dollár, ... European conference on computer vision, 740-755, 2014	1155	2014
Globally-optimal greedy algorithms for tracking a variable number of objects H Pirsiavash, D Ramanan, CC Fowlkes CVPR 2011, 1201-1208, 2011	1068	2011
Finding tiny faces P Hu, D Ramanan Proceedings of the IEEE conference on computer vision and pattern …, 2017	1015	2017
A large-scale benchmark dataset for event recognition in surveillance video S Oh, A Hoogs, A Perera, N Cuntoor, CC Chen, JT Lee, S Mukherjee, ... CVPR 2011, 3153-3160, 2011	986	2011
Detecting activities of daily living in first-person camera views H Pirsiavash, D Ramanan 2012 IEEE conference on computer vision and pattern recognition, 2847-2854, 2012	959	2012
Depth-supervised nerf: Fewer views and faster training for free K Deng, A Liu, JY Zhu, D Ramanan Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022	946	2022
Efficiently scaling up crowdsourced video annotation: A set of best practices for high quality, economical video labeling C Vondrick, D Patterson, D Ramanan International journal of computer vision 101, 184-204, 2013	827*	2013
Learning to model the tail YX Wang, D Ramanan, M Hebert Advances in neural information processing systems 30, 2017	813	2017
3d human pose estimation= 2d pose estimation+ matching CH Chen, D Ramanan Proceedings of the IEEE conference on computer vision and pattern …, 2017	714	2017
Learning to parse images of articulated bodies D Ramanan Advances in Neural Information Processing Systems 19, 1129, 2007	670*	2007
Discriminative models for multi-class object layout C Desai, D Ramanan, CC Fowlkes International journal of computer vision 95, 1-12, 2011	669	2011
Argoverse 2: Next generation datasets for self-driving perception and forecasting B Wilson, W Qi, T Agarwal, J Lambert, J Singh, S Khandelwal, B Pan, ... arXiv preprint arXiv:2301.00493, 2023	607	2023
Actionvlad: Learning spatio-temporal aggregation for action classification R Girdhar, D Ramanan, A Gupta, J Sivic, B Russell Proceedings of the IEEE conference on computer vision and pattern …, 2017	599	2017
Need for speed: A benchmark for higher frame rate object tracking H Kiani Galoogahi, A Fagg, C Huang, D Ramanan, S Lucey Proceedings of the IEEE international conference on computer vision, 1125-1134, 2017	553	2017

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