| Anomaly detection in crowded scenes V Mahadevan, W Li, V Bhalodia, N Vasconcelos 2010 IEEE computer society conference on computer vision and pattern …, 2010 | 1422 | 2010 |
| Anomaly detection and localization in crowded scenes W Li, V Mahadevan, N Vasconcelos IEEE transactions on pattern analysis and machine intelligence 36 (1), 18-32, 2013 | 828 | 2013 |
| The discriminant center-surround hypothesis for bottom-up saliency D Gao, V Mahadevan, N Vasconcelos Advances in neural information processing systems 20, 2007 | 553 | 2007 |
| Spatiotemporal saliency in dynamic scenes V Mahadevan, N Vasconcelos IEEE transactions on pattern analysis and machine intelligence 32 (1), 171-177, 2009 | 474 | 2009 |
| Saliency-based discriminant tracking V Mahadevan, N Vasconcelos 2009 IEEE conference on computer vision and pattern recognition, 1007-1013, 2009 | 250 | 2009 |
| Learning optimal seeds for diffusion-based salient object detection S Lu, V Mahadevan, N Vasconcelos Proceedings of the IEEE conference on computer vision and pattern …, 2014 | 152 | 2014 |
| Cluster canonical correlation analysis N Rasiwasia, D Mahajan, V Mahadevan, G Aggarwal Artificial intelligence and statistics, 823-831, 2014 | 151 | 2014 |
| Background subtraction in highly dynamic scenes V Mahadevan, N Vasconcelos 2008 IEEE Conference on Computer Vision and Pattern Recognition, 1-6, 2008 | 149 | 2008 |
| Biologically inspired object tracking using center-surround saliency mechanisms V Mahadevan, N Vasconcelos IEEE transactions on pattern analysis and machine intelligence 35 (3), 541-554, 2012 | 145 | 2012 |
| Robust model-based vasculature detection in noisy biomedical images V Mahadevan, H Narasimha-Iyer, B Roysam, HL Tanenbaum IEEE Transactions on Information Technology in Biomedicine 8 (3), 360-376, 2004 | 106 | 2004 |
| Decoder-side region of interest video processing KH El-Maleh, V Mahadevan, H Wang US Patent 8,315,466, 2012 | 89 | 2012 |
| Generalized Stauffer–Grimson background subtraction for dynamic scenes AB Chan, V Mahadevan, N Vasconcelos Machine Vision and Applications 22 (5), 751-766, 2011 | 87 | 2011 |
| Vlad3: Encoding dynamics of deep features for action recognition Y Li, W Li, V Mahadevan, N Vasconcelos Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 84 | 2016 |
| On the design of robust classifiers for computer vision H Masnadi-Shirazi, V Mahadevan, N Vasconcelos 2010 IEEE Computer Society Conference on Computer Vision and Pattern …, 2010 | 82 | 2010 |
| A novel approach to FRUC using discriminant saliency and frame segmentation N Jacobson, YL Lee, V Mahadevan, N Vasconcelos, TQ Nguyen IEEE Transactions on Image Processing 19 (11), 2924-2934, 2010 | 64 | 2010 |
| Improved detection of the central reflex in retinal vessels using a generalized dual-Gaussian model and robust hypothesis testing H Narasimha-Iyer, V Mahadevan, JM Beach, B Roysam IEEE Transactions on Information Technology in Biomedicine 12 (3), 406-410, 2008 | 50 | 2008 |
| Toward understanding catastrophic forgetting in continual learning CV Nguyen, A Achille, M Lam, T Hassner, V Mahadevan, S Soatto arXiv preprint arXiv:1908.01091, 2019 | 42 | 2019 |
| Deep convolutional neural networks for eigenvalue problems in mechanics D Finol, Y Lu, V Mahadevan, A Srivastava International Journal for Numerical Methods in Engineering 118 (5), 258-275, 2019 | 41 | 2019 |
| Maximum covariance unfolding: Manifold learning for bimodal data V Mahadevan, C Wong, J Pereira, T Liu, N Vasconcelos, L Saul Advances in Neural Information Processing Systems 24, 2011 | 38 | 2011 |
| A 2-D/3-D model-based method to quantify the complexity of microvasculature imaged by in vivo multiphoton microscopy JA Tyrrell, V Mahadevan, RT Tong, EB Brown, RK Jain, B Roysam Microvascular Research 70 (3), 165-178, 2005 | 36 | 2005 |
