| 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 | 2249 | 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 | 1180 | 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 | 779 | 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 | 639 | 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 | 361 | 2019 |
| 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 | 297 | 2012 |
| 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 | 266 | 2010 |
| On evaluation of embodied navigation agents P Anderson, A Chang, DS Chaplot, A Dosovitskiy, S Gupta, V Koltun, ... arXiv preprint arXiv:1807.06757, 2018 | 256 | 2018 |
| 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 | 218 | 2017 |
| 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 | 207 | 2011 |
| Characterizing structural relationships in scenes using graph kernels M Fisher, M Savva, P Hanrahan ACM SIGGRAPH 2011 papers, 1-12, 2011 | 192 | 2011 |
| 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 | 171 | 2017 |
| 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 | 129 | 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 | 123 | 2016 |
| 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 | 119 | 2019 |
| Deep Convolutional Priors for Indoor Scene Synthesis K Wang, M Savva, AX Chang, D Ritchie | 117 | 2018 |
| 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 | 92 | 2019 |
| 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 | 90 | 2019 |
| SceneGrok: Inferring action maps in 3D environments M Savva, AX Chang, P Hanrahan, M Fisher, M Nießner ACM transactions on graphics (TOG) 33 (6), 1-10, 2014 | 85 | 2014 |
| Text to 3d scene generation with rich lexical grounding A Chang, W Monroe, M Savva, C Potts, CD Manning arXiv preprint arXiv:1505.06289, 2015 | 84 | 2015 |
Angel ChangSimon Fraser UniversityVerified email at cs.stanford.edu
