nuscenes: A multimodal dataset for autonomous driving H Caesar, V Bankiti, AH Lang, S Vora, VE Liong, Q Xu, A Krishnan, Y Pan, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 4952 | 2020 |
Pointpillars: Fast encoders for object detection from point clouds AH Lang, S Vora, H Caesar, L Zhou, J Yang, O Beijbom Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 3372 | 2019 |
Compact bilinear pooling Y Gao, O Beijbom, N Zhang, T Darrell Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 1023 | 2016 |
Pointpainting: Sequential fusion for 3d object detection S Vora, AH Lang, B Helou, O Beijbom Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 834 | 2020 |
Covernet: Multimodal behavior prediction using trajectory sets T Phan-Minh, EC Grigore, FA Boulton, O Beijbom, EM Wolff Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 390 | 2020 |
Automated annotation of coral reef survey images O Beijbom, PJ Edmunds, DI Kline, BG Mitchell, D Kriegman Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on …, 2012 | 365 | 2012 |
Towards automated annotation of benthic survey images: Variability of human experts and operational modes of automation O Beijbom, PJ Edmunds, C Roelfsema, J Smith, DI Kline, BP Neal, ... PloS one 10 (7), e0130312, 2015 | 347 | 2015 |
Best Practices for Fine-tuning Visual Classifiers to New Domains B Chu, V Madhavan, O Beijbom, J Hoffman, T Darrell European Conference on Computer Vision, workshop on TASK-CV, 2016 | 186 | 2016 |
Menu-match: Restaurant-specific food logging from images O Beijbom, N Joshi, D Morris, S Saponas, S Khullar 2015 IEEE Winter Conference on Applications of Computer Vision, 844-851, 2015 | 160 | 2015 |
Panoptic nuscenes: A large-scale benchmark for lidar panoptic segmentation and tracking WK Fong, R Mohan, JV Hurtado, L Zhou, H Caesar, O Beijbom, A Valada IEEE Robotics and Automation Letters 7 (2), 3795-3802, 2022 | 147 | 2022 |
nuplan: A closed-loop ml-based planning benchmark for autonomous vehicles H Caesar, J Kabzan, KS Tan, WK Fong, E Wolff, A Lang, L Fletcher, ... arXiv preprint arXiv:2106.11810, 2021 | 145 | 2021 |
Multimodal trajectory prediction conditioned on lane-graph traversals N Deo, E Wolff, O Beijbom Conference on Robot Learning, 203-212, 2022 | 142 | 2022 |
Transfer learning and deep feature extraction for planktonic image data sets EC Orenstein, O Beijbom 2017 IEEE Winter Conference on Applications of Computer Vision (WACV), 1082-1088, 2017 | 123 | 2017 |
Monitoring of coral reefs using artificial intelligence: A feasible and cost-effective approach M Gonzalez-Rivero, O Beijbom, A Rodriguez-Ramirez, DEP Bryant, ... Remote Sensing 12 (3), 489, 2020 | 105 | 2020 |
Leveraging automated image analysis tools to transform our capacity to assess status and trends of coral reefs ID Williams, CS Couch, O Beijbom, TA Oliver, B Vargas-Angel, ... Frontiers in Marine Science 6, 420984, 2019 | 97 | 2019 |
The Catlin Seaview Survey–kilometre‐scale seascape assessment, and monitoring of coral reef ecosystems M González‐Rivero, P Bongaerts, O Beijbom, O Pizarro, A Friedman, ... Aquatic Conservation: Marine and Freshwater Ecosystems 24 (S2), 184-198, 2014 | 95 | 2014 |
Whoi-plankton-a large scale fine grained visual recognition benchmark dataset for plankton classification EC Orenstein, O Beijbom, EE Peacock, HM Sosik arXiv preprint arXiv:1510.00745, 2015 | 94 | 2015 |
Scaling up ecological measurements of coral reefs using semi-automated field image collection and analysis M González-Rivero, O Beijbom, A Rodriguez-Ramirez, T Holtrop, ... Remote Sensing 8 (1), 30, 2016 | 83 | 2016 |
Restaurant-specific food logging from images NS Joshi, S Khullar, TS Saponas, D Morris, O Beijbom US Patent 9,659,225, 2017 | 64 | 2017 |
Improving automated annotation of benthic survey images using wide-band fluorescence O Beijbom, T Treibitz, DI Kline, G Eyal, A Khen, B Neal, Y Loya, ... Scientific reports 6 (1), 23166, 2016 | 63 | 2016 |