S. Sankaranarayanan

发表

Generate to Adapt: Aligning Domains Using Generative Adversarial Networks

Carlos D. Castillo, Swami Sankaranarayanan, Rama Chellappa, 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

Triplet probabilistic embedding for face verification and clustering

Carlos D. Castillo, Swami Sankaranarayanan, Rama Chellappa, 2016, 2016 IEEE 8th International Conference on Biometrics Theory, Applications and Systems (BTAS).

Deep Learning for Understanding Faces: Machines May Be Just as Good, or Better, than Humans

Carlos D. Castillo, Vishal M. Patel, R. Chellappa, 2018, IEEE Signal Processing Magazine.

Automatic Detection of Exudates and Microaneurysms from Non-Dilated Diabetic Retinopathy Retinal Images

S. Sankaranarayanan, M. Bennet, 2014 .

Exploring Visual Prompts for Adapting Large-Scale Models

Phillip Isola, S. Sankaranarayanan, Ali Jahanian, 2022, 2203.17274.

Semantic uncertainty intervals for disentangled latent spaces

Anastasios Nikolas Angelopoulos, Phillip Isola, S. Sankaranarayanan, 2022, 2207.10074.

Semantic uncertainty intervals for disentangled latent spaces

Anastasios Nikolas Angelopoulos, Phillip Isola, S. Sankaranarayanan, 2022, NeurIPS.

Aging with GRACE: Lifelong Model Editing with Discrete Key-Value Adaptors

M. Ghassemi, S. Sankaranarayanan, H. Palangi, 2022, arXiv.org.

MetaReg: Towards Domain Generalization using Meta-Regularization

Swami Sankaranarayanan, Rama Chellappa, Yogesh Balaji, 2018, NeurIPS.

Learning from Synthetic Data: Addressing Domain Shift for Semantic Segmentation

Swami Sankaranarayanan, Rama Chellappa, Ser-Nam Lim, 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

Discrepancy Ratio: Evaluating Model Performance When Even Experts Disagree on the Truth

Swami Sankaranarayanan, Pouya Samangouei, Ardavan Saeedi, 2020, ICLR.

Learning From Noisy Labels by Regularized Estimation of Annotator Confusion

Swami Sankaranarayanan, Daniel C. Alexander, Ardavan Saeedi, 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Social Trait Information in Deep Convolutional Neural Networks Trained for Face Identification

Connor J. Parde, Carlos D. Castillo, Swami Sankaranarayanan, 2019, Cogn. Sci..

Unsupervised Domain Adaptation for Semantic Segmentation with GANs pdf

Swami Sankaranarayanan, Rama Chellappa, Ser-Nam Lim, 2017, ArXiv.

Towards the design of an end-to-end automated system for image and video-based recognition

Carlos D. Castillo, Swami Sankaranarayanan, Rama Chellappa, 2016, 2016 Information Theory and Applications Workshop (ITA).

Visual Prompting: Modifying Pixel Space to Adapt Pre-trained Models

Phillip Isola, S. Sankaranarayanan, Ali Jahanian, 2022, ArXiv.

An All-In-One Convolutional Neural Network for Face Analysis

Carlos D. Castillo, Swami Sankaranarayanan, Rama Chellappa, 2016, 2017 12th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2017).

Aging with GRACE: Lifelong Model Editing with Discrete Key-Value Adaptors

M. Ghassemi, S. Sankaranarayanan, H. Palangi, 2022, arXiv.org.

Swami Sankaranarayanan, Rama Chellappa, Azadeh Alavi, 2016, ArXiv.

Face recognition accuracy of forensic examiners, superrecognizers, and face recognition algorithms

Swami Sankaranarayanan, Rama Chellappa, Jun-Cheng Chen, 2018, Proceedings of the National Academy of Sciences.

Face and Image Representation in Deep CNN Features

Connor J. Parde, Carlos D. Castillo, Matthew Q. Hill, 2017, 2017 12th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2017).

Aging with GRACE: Lifelong Model Editing with Discrete Key-Value Adaptors

M. Ghassemi, S. Sankaranarayanan, H. Palangi, 2022, ArXiv.

Deep Learning for Understanding Faces: Machines May Be Just as Good, or Better, than Humans

Carlos D. Castillo, Swami Sankaranarayanan, Jun-Cheng Chen, 2018, IEEE Signal Processing Magazine.

An Efficient and Integrated Approach for the Detection of Blood Vessels and Exudates in Color Fundus Images

S. Sankaranarayanan, M. Bennet, N. Sathya, 2014 .

Aging with GRACE: Lifelong Model Editing with Discrete Key-Value Adaptors

M. Ghassemi, S. Sankaranarayanan, H. Palangi, 2022, ArXiv.

Crystal Loss and Quality Pooling for Unconstrained Face Verification and Recognition pdf

Carlos D. Castillo, Swami Sankaranarayanan, Rama Chellappa, 2018, ArXiv.

Unconstrained Still/Video-Based Face Verification with Deep Convolutional Neural Networks

Carlos D. Castillo, Swami Sankaranarayanan, Rama Chellappa, 2016, International Journal of Computer Vision.

Unconstrained face verification using fisher vectors computed from frontalized faces

Swami Sankaranarayanan, Rama Chellappa, Jun-Cheng Chen, 2015, 2015 IEEE 7th International Conference on Biometrics Theory, Applications and Systems (BTAS).

Regularizing deep networks using efficient layerwise adversarial training

Swami Sankaranarayanan, Rama Chellappa, Ser-Nam Lim, 2017, AAAI.

Learning From Noisy Labels by Regularized Estimation of Annotator Confusion

N. Silberman, S. Sankaranarayanan, Ryutaro Tanno, 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Proximity-Aware Hierarchical Clustering of unconstrained faces

Carlos D. Castillo, Swami Sankaranarayanan, Rama Chellappa, 2018, Image Vis. Comput..

Aging with GRACE: Lifelong Model Editing with Discrete Key-Value Adaptors

M. Ghassemi, S. Sankaranarayanan, H. Palangi, 2022, NeurIPS.

Real world relevance of generative counterfactual explanations

M. Ghassemi, Phillip Isola, S. Sankaranarayanan, 2022 .

SECURABLE IMAGE COMPRESSION USING SPIHT ALGORITHM

S. Sankaranarayanan, J. Suresh, 2013 .

Unsupervised Visual Domain Adaptation Using Generative Adversarial Networks

Swami Sankaranarayanan, Rama Chellappa, Yogesh Balaji, 2020, Computer Vision.