| Real-time grasp detection using convolutional neural networks J Redmon, A Angelova 2015 IEEE International Conference on Robotics and Automation (ICRA), 1316-1322, 2015 | 414 | 2015 |
| Unsupervised learning of depth and ego-motion from monocular video using 3d geometric constraints R Mahjourian, M Wicke, A Angelova Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 342 | 2018 |
| Computer vision on Mars L Matthies, M Maimone, A Johnson, Y Cheng, R Willson, C Villalpando, ... International Journal of Computer Vision 75 (1), 67-92, 2007 | 227 | 2007 |
| Real-time pedestrian detection with deep network cascades A Angelova, A Krizhevsky, V Vanhoucke, A Ogale, D Ferguson | 225 | 2015 |
| Efficient object detection and segmentation for fine-grained recognition A Angelova, S Zhu Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2013 | 224 | 2013 |
| Learning and prediction of slip from visual information A Angelova, L Matthies, D Helmick, P Perona Journal of Field Robotics 24 (3), 205-231, 2007 | 143 | 2007 |
| Pruning training sets for learning of object categories A Angelova, Y Abu-Mostafam, P Perona 2005 IEEE Computer Society Conference on Computer Vision and Pattern …, 2005 | 138 | 2005 |
| Depth prediction without the sensors: Leveraging structure for unsupervised learning from monocular videos V Casser, S Pirk, R Mahjourian, A Angelova Proceedings of the AAAI Conference on Artificial Intelligence 33, 8001-8008, 2019 | 131 | 2019 |
| Terrain adaptive navigation for planetary rovers D Helmick, A Angelova, L Matthies Journal of Field Robotics 26 (4), 391-410, 2009 | 111 | 2009 |
| Pedestrian detection with a large-field-of-view deep network A Angelova, A Krizhevsky, V Vanhoucke 2015 IEEE international conference on robotics and automation (ICRA), 704-711, 2015 | 100 | 2015 |
| Fast terrain classification using variable-length representation for autonomous navigation A Angelova, L Matthies, D Helmick, P Perona 2007 IEEE Conference on Computer Vision and Pattern Recognition, 1-8, 2007 | 96 | 2007 |
| Learning to predict slip for ground robots A Angelova, L Matthies, D Helmick, G Sibley, P Perona Proceedings 2006 IEEE International Conference on Robotics and Automation …, 2006 | 86 | 2006 |
| Depth from videos in the wild: Unsupervised monocular depth learning from unknown cameras A Gordon, H Li, R Jonschkowski, A Angelova Proceedings of the IEEE International Conference on Computer Vision, 8977-8986, 2019 | 80 | 2019 |
| Towards learned traversability for robot navigation: From underfoot to the far field A Howard, M Turmon, L Matthies, B Tang, A Angelova, E Mjolsness Journal of Field Robotics 23 (11‐12), 1005-1017, 2006 | 72 | 2006 |
| Slip prediction using visual information A Angelova, L Matthies, D Helmick, P Perona MIT Press, 2007 | 62 | 2007 |
| Image segmentation for large-scale subcategory flower recognition A Angelova, S Zhu, Y Lin 2013 IEEE Workshop on Applications of Computer Vision (WACV), 39-45, 2013 | 59 | 2013 |
| Improved generator objectives for gans B Poole, AA Alemi, J Sohl-Dickstein, A Angelova arXiv preprint arXiv:1612.02780, 2016 | 46 | 2016 |
| Epicyclic transmission for zero turning radius vehicles JP Deschamps, JF Peterson US Patent 6,641,497, 2003 | 43* | 2003 |
| Deep value networks learn to evaluate and iteratively refine structured outputs M Gygli, M Norouzi, A Angelova arXiv preprint arXiv:1703.04363, 2017 | 39 | 2017 |
| Geometry-based next frame prediction from monocular video R Mahjourian, M Wicke, A Angelova 2017 IEEE Intelligent Vehicles Symposium (IV), 1700-1707, 2017 | 30 | 2017 |
Daniel HelmickToyota Research InstituteVerified email at tri.global
