Manolis Savva

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Angel ChangSimon Fraser UniversityDirección de correo verificada de cs.stanford.edu
Thomas FunkhouserPrinceton UniversityDirección de correo verificada de cs.princeton.edu
Patrick HanrahanStanford UniversityDirección de correo verificada de cs.stanford.edu
Dhruv BatraFAIR (Meta AI) | Georgia TechDirección de correo verificada de gatech.edu
Shuran SongColumbia UniversityDirección de correo verificada de cs.columbia.edu
Matthias NießnerProfessor of Computer Science, Technical University of MunichDirección de correo verificada de tum.de
Erik WijmansAppleDirección de correo verificada de apple.com
Hao SuUCSD CSEDirección de correo verificada de ucsd.edu
Fisher YuETH ZurichDirección de correo verificada de ethz.ch
Matthew FisherPrincipal Research Scientist, Adobe ResearchDirección de correo verificada de cs.stanford.edu
Silvio SavareseAssociate Professor of Computer Science at Stanford UniversityDirección de correo verificada de stanford.edu
Vladlen KoltunDistinguished Scientist, AppleDirección de correo verificada de apple.com
Andy ZengResearch Scientist, GoogleDirección de correo verificada de google.com
Abhishek KadianMetaDirección de correo verificada de meta.com
Leonidas GuibasProfessor of Computer Science, Stanford UniversityDirección de correo verificada de cs.stanford.edu
Angela DaiTechnical University of MunichDirección de correo verificada de tum.de
Daniel RitchieBrown UniversityDirección de correo verificada de brown.edu
Li YiTsinghua UniversityDirección de correo verificada de mail.tsinghua.edu.cn
Qixing HuangAssociate Professor of Computer Science, UT AustinDirección de correo verificada de cs.utexas.edu
Maciej HalberPrinceton UniversityDirección de correo verificada de cs.princeton.edu

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Manolis Savva

Simon Fraser University

Dirección de correo verificada de sfu.ca - Página principal

Computer Graphics Computer Vision Machine Learning Embodied AI


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
Shapenet: An information-rich 3d model repository AX Chang, T Funkhouser, L Guibas, P Hanrahan, Q Huang, Z Li, ... arXiv preprint arXiv:1512.03012, 2015	4352	2015
Scannet: Richly-annotated 3d reconstructions of indoor scenes A Dai, AX Chang, M Savva, M Halber, T Funkhouser, M Nießner Proceedings of the IEEE conference on computer vision and pattern …, 2017	2770	2017
Matterport3d: Learning from rgb-d data in indoor environments A Chang, A Dai, T Funkhouser, M Halber, M Niessner, M Savva, S Song, ... arXiv preprint arXiv:1709.06158, 2017	1390	2017
Semantic scene completion from a single depth image S Song, F Yu, A Zeng, AX Chang, M Savva, T Funkhouser Proceedings of the IEEE conference on computer vision and pattern …, 2017	1139	2017
Habitat: A platform for embodied ai research M Savva, A Kadian, O Maksymets, Y Zhao, E Wijmans, B Jain, J Straub, ... Proceedings of the IEEE/CVF international conference on computer vision …, 2019	976	2019
On evaluation of embodied navigation agents P Anderson, A Chang, DS Chaplot, A Dosovitskiy, S Gupta, V Koltun, ... arXiv preprint arXiv:1807.06757, 2018	554	2018
Example-based synthesis of 3D object arrangements M Fisher, D Ritchie, M Savva, T Funkhouser, P Hanrahan ACM Transactions on Graphics (TOG) 31 (6), 1-11, 2012	381	2012
The Replica dataset: A digital replica of indoor spaces J Straub, T Whelan, L Ma, Y Chen, E Wijmans, S Green, JJ Engel, ... arXiv preprint arXiv:1906.05797, 2019	368	2019
Dd-ppo: Learning near-perfect pointgoal navigators from 2.5 billion frames E Wijmans, A Kadian, A Morcos, S Lee, I Essa, D Parikh, M Savva, ... arXiv preprint arXiv:1911.00357, 2019	316	2019
Revision: Automated classification, analysis and redesign of chart images M Savva, N Kong, A Chhajta, L Fei-Fei, M Agrawala, J Heer Proceedings of the 24th annual ACM symposium on User interface software and …, 2011	307	2011
Back-action-evading measurements of nanomechanical motion JB Hertzberg, T Rocheleau, T Ndukum, M Savva, AA Clerk, KC Schwab Nature Physics 6 (3), 213-217, 2010	300	2010
Physically-based rendering for indoor scene understanding using convolutional neural networks Y Zhang, S Song, E Yumer, M Savva, JY Lee, H Jin, T Funkhouser Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017	284	2017
MINOS: Multimodal indoor simulator for navigation in complex environments M Savva, AX Chang, A Dosovitskiy, T Funkhouser, V Koltun arXiv preprint arXiv:1712.03931, 2017	252	2017
Habitat 2.0: Training home assistants to rearrange their habitat A Szot, A Clegg, E Undersander, E Wijmans, Y Zhao, J Turner, N Maestre, ... Advances in Neural Information Processing Systems 34, 251-266, 2021	242	2021
Characterizing structural relationships in scenes using graph kernels M Fisher, M Savva, P Hanrahan ACM SIGGRAPH 2011 papers, 1-12, 2011	242	2011
Deep Convolutional Priors for Indoor Scene Synthesis K Wang, M Savva, AX Chang, D Ritchie	196	2018
Scan2cad: Learning cad model alignment in rgb-d scans A Avetisyan, M Dahnert, A Dai, M Savva, AX Chang, M Nießner Proceedings of the IEEE/CVF Conference on computer vision and pattern …, 2019	193	2019
Learning spatial knowledge for text to 3D scene generation A Chang, M Savva, CD Manning Proceedings of the 2014 conference on empirical methods in natural language …, 2014	172	2014
Shrec16 track: largescale 3d shape retrieval from shapenet core55 M Savva, F Yu, H Su, M Aono, B Chen, D Cohen-Or, W Deng, H Su, S Bai, ... Proceedings of the eurographics workshop on 3D object retrieval 10, 2016	156	2016
Text2shape: Generating shapes from natural language by learning joint embeddings K Chen, CB Choy, M Savva, AX Chang, T Funkhouser, S Savarese Computer Vision–ACCV 2018: 14th Asian Conference on Computer Vision, Perth …, 2019	149	2019

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