| Weakly Supervised Instance Segmentation using Class Peak Response Y Zhou, Y Zhu, Q Ye, Q Qiu, J Jiao CVPR 2018 arXiv:1804.00880, 2018 | 373 | 2018 |
| Oriented response networks Y Zhou, Q Ye, Q Qiu, J Jiao Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017 | 358 | 2017 |
| Lanenet: Real-time lane detection networks for autonomous driving Z Wang, W Ren, Q Qiu arXiv preprint arXiv:1807.01726, 2018 | 338 | 2018 |
| Subspace interpolation via dictionary learning for unsupervised domain adaptation J Ni, Q Qiu, R Chellappa Proceedings of the IEEE conference on computer vision and pattern …, 2013 | 217 | 2013 |
| Learning to Learn with Variational Information Bottleneck for Domain Generalization Y Du, J Xu, H Xiong, Q Qiu, X Zhen, CGM Snoek, L Shao ECCV 2020. arXiv preprint arXiv:2007.07645, 2020 | 212 | 2020 |
| Sparse dictionary-based representation and recognition of action attributes Q Qiu, Z Jiang, R Chellappa 2011 international conference on computer vision, 707-714, 2011 | 189 | 2011 |
| Soft proposal networks for weakly supervised object localization Y Zhu, Y Zhou, Q Ye, Q Qiu, J Jiao Proceedings of the IEEE international conference on computer vision, 1841-1850, 2017 | 181 | 2017 |
| Not afraid of the dark: Nir-vis face recognition via cross-spectral hallucination and low-rank embedding J Lezama, Q Qiu, G Sapiro Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 174 | 2017 |
| Domain adaptive dictionary learning Q Qiu, VM Patel, P Turaga, R Chellappa European Conference on Computer Vision, 631-645, 2012 | 155 | 2012 |
| Computer vision analysis captures atypical attention in toddlers with autism K Campbell, KLH Carpenter, J Hashemi, S Espinosa, S Marsan, JS Borg, ... Autism 23 (3), 619-628, 2019 | 133 | 2019 |
| Automatic emotion and attention analysis of young children at home: a ResearchKit autism feasibility study HL Egger, G Dawson, J Hashemi, KLH Carpenter, S Espinosa, ... Nature Digital Medicine 1 (1), 20, 2018 | 129 | 2018 |
| Ole: Orthogonal low-rank embedding-a plug and play geometric loss for deep learning J Lezama, Q Qiu, P Musé, G Sapiro Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 115 | 2018 |
| Computer vision analysis for quantification of autism risk behaviors J Hashemi, G Dawson, KLH Carpenter, K Campbell, Q Qiu, S Espinosa, ... IEEE Transactions on Affective Computing 12 (1), 215-226, 2021 | 104 | 2021 |
| Learning transformations for clustering and classification Q Qiu, G Sapiro Journal of Machine Learning Research 16 (Feb), 187−225, 2015 | 101 | 2015 |
| Structure-Preserving Sparse Decomposition for Expression Analysis S Taheri, Q Qiu, R Chellappa Transactions on Image Processing 23 (8), 3590 - 3603, 2014 | 100* | 2014 |
| Use of a digital modified checklist for autism in toddlers–revised with follow-up to improve quality of screening for autism K Campbell, KLH Carpenter, S Espinosa, J Hashemi, Q Qiu, M Tepper, ... The Journal of pediatrics 183, 133-139. e1, 2017 | 98 | 2017 |
| Shared storage network system and a method for operating a shared storage network system Q Qiu, J Biswas US Patent 7,797,393, 2010 | 97 | 2010 |
| DCFNet: Deep Neural Network with Decomposed Convolutional Filters Q Qiu, X Cheng, R Calderbank, G Sapiro International Conference on Machine Learning, ICML 2018, 2018 | 89 | 2018 |
| Adversarially learned representations for information obfuscation and inference M Bertran, N Martinez, A Papadaki, Q Qiu, M Rodrigues, G Reeves, ... International Conference on Machine Learning, 614-623, 2019 | 86 | 2019 |
| Information-theoretic dictionary learning for image classification Q Qiu, V Patel, R Chellappa IEEE Transaction on Pattern Analysis and Machine Intelligence 36 (11), 2173-2184, 2014 | 77 | 2014 |
Guillermo SapiroAugustine Family Professor, Princeton University; Distinguished Eng., Apple; Prof. Emeritus, Duke U.Verified email at princeton.edu
