Swami Sankaranarayanan
Swami Sankaranarayanan
Postdoctoral Associate, CSAIL, MIT
Verified email at - Homepage
Cited by
Cited by
Generate To Adapt: Aligning Domains using Generative Adversarial Networks
S Sankaranarayanan, Y Balaji, CD Castillo, R Chellappa
Computer Vision and Pattern Recognition (CVPR) 2018, 2018
An all-in-one convolutional neural network for face analysis
R Ranjan, S Sankaranarayanan, CD Castillo, R Chellappa
Automatic Face & Gesture Recognition (FG 2017), 2017 12th IEEE International …, 2017
Learning from Synthetic Data: Addressing Domain Shift for Semantic Segmentation
S Sankaranarayanan, Y Balaji, A Jain, SN Lim, R Chellappa
Computer Vision and Pattern Recognition (CVPR) 2018, 2018
MetaReg: Towards Domain Generalization using Meta-Regularization
Y Balaji, S Sankaranarayanan, R Chellappa
Advances in Neural Information Processing Systems (NeurIPS), 1004-1014, 2018
Triplet probabilistic embedding for face verification and clustering
S Sankaranarayanan, A Alavi, CD Castillo, R Chellappa
Biometrics Theory, Applications and Systems (BTAS), 2016 IEEE 8th …, 2016
Face recognition accuracy of forensic examiners, superrecognizers, and face recognition algorithms
PJ Phillips, AN Yates, Y Hu, CA Hahn, E Noyes, K Jackson, JG Cavazos, ...
Proceedings of the National Academy of Sciences (PNAS), 201721355, 2018
Deep Learning for Understanding Faces: Machines May Be Just as Good, or Better, than Humans
R Ranjan, S Sankaranarayanan, A Bansal, N Bodla, JC Chen, VM Patel, ...
IEEE Signal Processing Magazine 35 (1), 66-83, 2018
Learning From Noisy Labels By Regularized Estimation Of Annotator Confusion
R Tanno, A Saeedi, S Sankaranarayanan, DC Alexander, N Silberman
Computer Vision and Pattern Recognition (CVPR) 2019, 2019
Triplet similarity embedding for face verification
S Sankaranarayanan, A Alavi, R Chellappa
arXiv preprint arXiv:1602.03418, 2016
Regularizing deep networks using efficient layerwise adversarial training
S Sankaranarayanan, A Jain, R Chellappa, SN Lim
Association for Advancement of Artificial Intelligence (AAAI) 2018, 2018
Unconstrained Still/Video-Based Face Verification with Deep Convolutional Neural Networks
JC Chen, R Ranjan, S Sankaranarayanan, A Kumar, CH Chen, VM Patel, ...
International Journal of Computer Vision, 1-20, 2017
KT Arpit Jain, Swaminathan Sankaranarayanan, David Scott Diwinsky, Ser Nam Lim
US Patent US 2018 / 0253866 A1, 2018
Unconstrained face verification using fisher vectors computed from frontalized faces
JC Chen, S Sankaranarayanan, VM Patel, R Chellappa
Biometrics Theory, Applications and Systems (BTAS), 2015 IEEE 7th …, 2015
Deep Convolutional Neural Network Features and the Original Image
CJ Parde, C Castillo, MQ Hill, YI Colon, S Sankaranarayanan, JC Chen, ...
arXiv preprint arXiv:1611.01751, 2016
Towards the design of an end-to-end automated system for image and video-based recognition
R Chellappa, JC Chen, R Ranjan, S Sankaranarayanan, A Kumar, ...
Information Theory and Applications Workshop (ITA), 2016, 1-7, 2016
Proximity-Aware Hierarchical Clustering of Unconstrained Faces
WA Lin, JC Chen, R Ranjan, A Bansal, S Sankaranarayanan, CD Castillo, ...
Image and Vision Computing, 2018
Guided Perturbations: Self Corrective Behavior in Convolutional Neural Networks
S Sankaranarayanan, A Jain, NY Niskayuna, SN Lim
International Conference in Computer Vision (ICCV 2017), 2017
Qualitative evaluation of detection and tracking performance
S Sankaranarayanan, F Bremond, D Tax
Advanced Video and Signal-Based Surveillance (AVSS), 2012 IEEE Ninth …, 2012
Discrepancy Ratio: Evaluating Model Performance When Even Experts Disagree on the Truth
I Lovchinsky, A Daks, I Malkin, P Samangouei, A Saeedi, Y Liu, ...
International Conference on Learning Representations, 2019
Visual Prompting: Modifying Pixel Space to Adapt Pre-trained Models
H Bahng, A Jahanian*, S Sankaranarayanan*, P Isola
arXiv preprint arXiv:2203.17274, 2022
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