| DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation JJ Park, P Florence, J Straub, R Newcombe, S Lovegrove Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019 | 4088 | 2019 |
| 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 | 1550 | 2019 |
| 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 | 868 | 2019 |
| Deep local shapes: Learning local sdf priors for detailed 3d reconstruction R Chabra, JE Lenssen, E Ilg, T Schmidt, J Straub, S Lovegrove, ... Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 499 | 2020 |
| StereoDRNet: Dilated Residual StereoNet R Chabra, J Straub, C Sweeney, R Newcombe, H Fuchs Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019 | 116 | 2019 |
| Omni3D: A Large Benchmark and Model for 3D Object Detection in the Wild G Brazil, A Kumar, J Straub, N Ravi, J Johnson, G Gkioxari Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 92 | 2023 |
| Frodo: From detections to 3d objects M Runz, K Li, M Tang, L Ma, C Kong, T Schmidt, I Reid, L Agapito, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 89* | 2020 |
| A Mixture of Manhattan Frames: Beyond the Manhattan World J Straub, G Rosman, O Freifeld, JJ Leonard, JW Fisher III CVPR, 2014 | 89 | 2014 |
| Orienternet: Visual localization in 2d public maps with neural matching PE Sarlin, D DeTone, TY Yang, A Avetisyan, J Straub, T Malisiewicz, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 70 | 2023 |
| A Dirichlet Process Mixture Model for Spherical Data J Straub, J Chang, O Freifeld, JW Fisher III Proceedings of the Eighteenth International Conference on Artificial …, 2015 | 68 | 2015 |
| The Manhattan Frame Model–Manhattan World Inference in the Space of Surface Normals J Straub, O Freifeld, G Rosman, JJ Leonard, JW Fisher IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017 | 66 | 2017 |
| Reconstructing scenes with mirror and glass surfaces. T Whelan, M Goesele, SJ Lovegrove, J Straub, S Green, R Szeliski, ... ACM Trans. Graph. 37 (4), 102:1-102:11, 2018 | 64 | 2018 |
| Project Aria: A new tool for egocentric multi-modal ai research J Engel, K Somasundaram, M Goesele, A Sun, A Gamino, A Turner, ... arXiv preprint arXiv:2308.13561, 2023 | 61 | 2023 |
| Efficient Global Point Cloud Alignment using Bayesian Nonparametric Mixtures J Straub, T Campbell, JP How, JW Fisher III arXiv preprint arXiv:1603.04868, 2016 | 56 | 2016 |
| Fast Relocalization for Visual Odometry using Binary Features J Straub, S Hilsenbeck, G Schroth, R Huitl, A Möller, E Steinbach Image Processing (ICIP), 2013 20th IEEE International Conference on, 2548-2552, 2013 | 50 | 2013 |
| Real-time Manhattan World Rotation Estimation in 3D J Straub, N Bhandari, JJ Leonard, JW Fisher III IROS, 2015 | 45 | 2015 |
| Streaming, distributed variational inference for Bayesian nonparametrics T Campbell, J Straub, JW Fisher III, JP How Advances in Neural Information Processing Systems 28, 280-288, 2015 | 40 | 2015 |
| Semantically-Aware Aerial Reconstruction from Multi-Modal Data R Cabezas, J Straub, JW Fisher III International Conference on Computer Vision (ICCV), 2015 | 37 | 2015 |
| Small-Variance Nonparametric Clustering on the Hypersphere J Straub, T Campbell, JP How, JW Fisher Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2015 | 36 | 2015 |
| Saliency detection and model-based tracking: a two part vision system for small robot navigation in forested environment R Roberts, DN Ta, J Straub, K Ok, F Dellaert Proc. of SPIE Vol 8387, 83870S-1, 2012 | 36 | 2012 |
Richard NewcombeVP, Research Science at Reality Labs ResearchVerified email at cs.washington.edu
