| Fast and accurate k-means for large datasets M Shindler, A Wong, A Meyerson Advances in neural information processing systems 24, 2011 | 205 | 2011 |
| Dense depth posterior (ddp) from single image and sparse range Y Yang, A Wong, S Soatto Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 99 | 2019 |
| Bilateral cyclic constraint and adaptive regularization for unsupervised monocular depth prediction A Wong, S Soatto Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 72 | 2019 |
| Umlsbert: Clinical domain knowledge augmentation of contextual embeddings using the unified medical language system metathesaurus G Michalopoulos, Y Wang, H Kaka, H Chen, A Wong arXiv preprint arXiv:2010.10391, 2020 | 68 | 2020 |
| Unsupervised Depth Completion From Visual Inertial Odometry A Wong, X Fei, S Tsuei, S Soatto IEEE Robotics and Automation Letters 5 (2), 1899-1906, 2020 | 68 | 2020 |
| Geo-supervised visual depth prediction X Fei, A Wong, S Soatto IEEE Robotics and Automation Letters 4 (2), 1661-1668, 2019 | 56 | 2019 |
| One shot learning via compositions of meaningful patches A Wong, AL Yuille Proceedings of the IEEE International Conference on Computer Vision, 1197-1205, 2015 | 47 | 2015 |
| Fluorescence microscopy image noise reduction using a stochastically-connected random field model SA Haider, A Cameron, P Siva, D Lui, MJ Shafiee, A Boroomand, ... Scientific reports 6 (1), 1-16, 2016 | 43 | 2016 |
| Unsupervised depth completion with calibrated backprojection layers A Wong, S Soatto Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 38 | 2021 |
| Learning topology from synthetic data for unsupervised depth completion A Wong, S Cicek, S Soatto IEEE Robotics and Automation Letters 6 (2), 1495-1502, 2021 | 28 | 2021 |
| Targeted adversarial perturbations for monocular depth prediction A Wong, S Cicek, S Soatto Advances in neural information processing systems 33, 8486-8497, 2020 | 28 | 2020 |
| Towards computer-aided severity assessment via deep neural networks for geographic and opacity extent scoring of SARS-CoV-2 chest X-rays A Wong, ZQ Lin, L Wang, AG Chung, B Shen, A Abbasi, ... Scientific reports 11 (1), 9315, 2021 | 22 | 2021 |
| An adaptive framework for learning unsupervised depth completion A Wong, X Fei, BW Hong, S Soatto IEEE Robotics and Automation Letters 6 (2), 3120-3127, 2021 | 20 | 2021 |
| Stereopagnosia: Fooling stereo networks with adversarial perturbations A Wong, M Mundhra, S Soatto Proceedings of the AAAI Conference on Artificial Intelligence 35 (4), 2879-2888, 2021 | 18 | 2021 |
| Comparative analysis of gait speed estimation using wideband and narrowband radars, thermal camera, and motion tracking suit technologies PP Morita, AS Rocha, G Shaker, D Lee, J Wei, B Fong, A Thatte, A Karimi, ... Journal of Healthcare Informatics Research 4, 215-237, 2020 | 9 | 2020 |
| Fidelity-Naturalness Evaluation of Single Image Super Resolution X Dong, Y Zhu, WL Li, L Xie, A Wong, A Yuille arXiv preprint arXiv:1511.06834, 2015 | 8* | 2015 |
| Not Just Streaks: Towards Ground Truth for Single Image Deraining Y Ba, H Zhang, E Yang, A Suzuki, A Pfahnl, CC Chandrappa, CM de Melo, ... Computer Vision–ECCV 2022: 17th European Conference, Tel Aviv, Israel …, 2022 | 7 | 2022 |
| Monitored distillation for positive congruent depth completion TY Liu, P Agrawal, A Chen, BW Hong, A Wong Computer Vision–ECCV 2022: 17th European Conference, Tel Aviv, Israel …, 2022 | 7 | 2022 |
| Voiced: Depth completion from inertial odometry and vision AYF Wong, X Fei, S Soatto arXiv preprint arXiv:1905.08616, 2019 | 7 | 2019 |
| Stereoscopic universal perturbations across different architectures and datasets Z Berger, P Agrawal, TY Liu, S Soatto, A Wong Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 6 | 2022 |
Stefano SoattoProfessor of Computer Science, UCLA; VP, AWSVerified email at ucla.edu
