| Pseudo-LiDAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving Y Wang, WL Chao, D Garg, B Hariharan, M Campbell, K Weinberger CVPR 2019, 2019 | 912 | 2019 |
| Synthesized classifiers for zero-shot learning S Changpinyo, WL Chao, B Gong, F Sha Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 866 | 2016 |
| Video summarization with long short-term memory K Zhang, WL Chao, F Sha, K Grauman Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016 | 693 | 2016 |
| An empirical study and analysis of generalized zero-shot learning for object recognition in the wild WL Chao, S Changpinyo, B Gong, F Sha Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016 | 581 | 2016 |
| Diverse sequential subset selection for supervised video summarization B Gong, WL Chao, K Grauman, F Sha Advances in neural information processing systems 27, 2014 | 481 | 2014 |
| Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Driving Y You, Y Wang, WL Chao, D Garg, G Pleiss, B Hariharan, M Campbell, ... International Conference on Learning Representations (ICLR), 2020 | 339 | 2020 |
| Simpleshot: Revisiting nearest-neighbor classification for few-shot learning Y Wang, WL Chao, KQ Weinberger, L Van Der Maaten arXiv preprint arXiv:1911.04623, 2019 | 269 | 2019 |
| Summary transfer: Exemplar-based subset selection for video summarization K Zhang, WL Chao, F Sha, K Grauman Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 240 | 2016 |
| Facial age estimation based on label-sensitive learning and age-oriented regression WL Chao, JZ Liu, JJ Ding Pattern Recognition 46 (3), 628-641, 2013 | 209 | 2013 |
| Predicting visual exemplars of unseen classes for zero-shot learning S Changpinyo, WL Chao, F Sha International Conference on Computer Vision, 2017 | 192 | 2017 |
| End-to-End Pseudo-LiDAR for Image-Based 3D Object Detection R Qian, D Garg, Y Wang, Y You, S Belongie, B Hariharan, M Campbell, ... CVPR 2020, 2020 | 169 | 2020 |
| FedBE: Making bayesian model ensemble applicable to federated learning HY Chen, WL Chao International Conference on Learning Representations (ICLR), 2021 | 161 | 2021 |
| Facial expression recognition based on improved local binary pattern and class-regularized locality preserving projection WL Chao, JJ Ding, JZ Liu Signal Processing 117, 1-10, 2015 | 128 | 2015 |
| A New Defense Against Adversarial Images: Turning a Weakness into a Strength S Hu, T Yu, C Guo, WL Chao, KQ Weinberger Conference on Neural Information Processing Systems (NeurIPS), 2019 | 108 | 2019 |
| Train in germany, test in the usa: Making 3d object detectors generalize Y Wang, X Chen, Y You, LE Li, B Hariharan, M Campbell, KQ Weinberger, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 105 | 2020 |
| On Bridging Generic and Personalized Federated Learning for Image Classification HY Chen, WL Chao International Conference on Learning Representations, 2022 | 80 | 2022 |
| Identifying and compensating for feature deviation in imbalanced deep learning HJ Ye, HY Chen, DC Zhan, WL Chao arXiv preprint arXiv:2001.01385, 2020 | 62 | 2020 |
| Deep Co-Training with Task Decomposition for Semi-Supervised Domain Adaptation L Yang, Y Wang, M Gao, A Shrivastava, KQ Weinberger, WL Chao, ... ICCV 2021, 2021 | 60 | 2021 |
| Face recognition WL Chao GICE, National Taiwan University, 2010 | 58 | 2010 |
| Large-Margin Determinantal Point Processes WL Chao, B Gong, K Grauman, F Sha Conference on Uncertainty in Artificial Intelligence (UAI), 2015 | 57* | 2015 |
Kilian WeinbergerCornell UniversityVerified email at cornell.edu
