| Image de-raining using a conditional generative adversarial network H Zhang, V Sindagi, VM Patel IEEE transactions on circuits and systems for video technology 30 (11), 3943 …, 2019 | 1166 | 2019 |
| Generating high-quality crowd density maps using contextual pyramid cnns VA Sindagi, VM Patel Proceedings of the IEEE international conference on computer vision, 1861-1870, 2017 | 745 | 2017 |
| A survey of recent advances in cnn-based single image crowd counting and density estimation VA Sindagi, VM Patel Pattern Recognition Letters 107, 3-16, 2018 | 609 | 2018 |
| Cnn-based cascaded multi-task learning of high-level prior and density estimation for crowd counting VA Sindagi, VM Patel 2017 14th IEEE international conference on advanced video and signal based …, 2017 | 603 | 2017 |
| Mvx-net: Multimodal voxelnet for 3d object detection VA Sindagi, Y Zhou, O Tuzel 2019 International Conference on Robotics and Automation (ICRA), 7276-7282, 2019 | 396 | 2019 |
| Ha-ccn: Hierarchical attention-based crowd counting network VA Sindagi, VM Patel IEEE Transactions on Image Processing 29, 323-335, 2019 | 230 | 2019 |
| Jhu-crowd++: Large-scale crowd counting dataset and a benchmark method VA Sindagi, R Yasarla, VM Patel IEEE transactions on pattern analysis and machine intelligence 44 (5), 2594-2609, 2020 | 229 | 2020 |
| Multi-level bottom-top and top-bottom feature fusion for crowd counting VA Sindagi, VM Patel Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 212 | 2019 |
| Syn2real transfer learning for image deraining using gaussian processes R Yasarla, VA Sindagi, VM Patel Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 196 | 2020 |
| Mega-cda: Memory guided attention for category-aware unsupervised domain adaptive object detection V Vs, V Gupta, P Oza, VA Sindagi, VM Patel Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 180 | 2021 |
| Multi-scale single image dehazing using perceptual pyramid deep network H Zhang, V Sindagi, VM Patel Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 178 | 2018 |
| Kiu-net: Overcomplete convolutional architectures for biomedical image and volumetric segmentation JMJ Valanarasu, VA Sindagi, I Hacihaliloglu, VM Patel IEEE Transactions on Medical Imaging 41 (4), 965-976, 2021 | 176 | 2021 |
| Kiu-net: Towards accurate segmentation of biomedical images using over-complete representations JMJ Valanarasu, VA Sindagi, I Hacihaliloglu, VM Patel Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020 | 172 | 2020 |
| Ntire 2018 challenge on image dehazing: Methods and results C Ancuti, CO Ancuti, R Timofte Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 171 | 2018 |
| High-quality facial photo-sketch synthesis using multi-adversarial networks L Wang, V Sindagi, V Patel 2018 13th IEEE international conference on automatic face & gesture …, 2018 | 156 | 2018 |
| Joint transmission map estimation and dehazing using deep networks H Zhang, V Sindagi, VM Patel IEEE Transactions on Circuits and Systems for Video Technology 30 (7), 1975-1986, 2019 | 151 | 2019 |
| Prior-based domain adaptive object detection for hazy and rainy conditions VA Sindagi, P Oza, R Yasarla, VM Patel Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 139 | 2020 |
| Unsupervised domain adaptation of object detectors: A survey P Oza, VA Sindagi, VV Sharmini, VM Patel IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023 | 128 | 2023 |
| Pushing the frontiers of unconstrained crowd counting: New dataset and benchmark method VA Sindagi, R Yasarla, VM Patel Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 106 | 2019 |
| Pushing the limits of unconstrained face detection: a challenge dataset and baseline results H Nada, VA Sindagi, H Zhang, VM Patel 2018 IEEE 9th international conference on biometrics theory, applications …, 2018 | 92 | 2018 |
Vishal M. PatelAssociate Professor, ECE, Johns Hopkins University在 jhu.edu 的电子邮件经过验证
