Search Results for author: Carlos D. Castillo

Found 31 papers, 6 papers with code

Towards the Design of an End-to-End Automated System for Image and Video-based Recognition

no code implementations28 Jan 2016 Rama Chellappa, Jun-Cheng Chen, Rajeev Ranjan, Swami Sankaranarayanan, Amit Kumar, Vishal M. Patel, Carlos D. Castillo

In this paper, we present a brief history of developments in computer vision and artificial neural networks over the last forty years for the problem of image-based recognition.

Face Verification Object +3

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

no code implementations9 May 2016 Jun-Cheng Chen, Rajeev Ranjan, Swami Sankaranarayanan, Amit Kumar, Ching-Hui Chen, Vishal M. Patel, Carlos D. Castillo, Rama Chellappa

Over the last five years, methods based on Deep Convolutional Neural Networks (DCNNs) have shown impressive performance improvements for object detection and recognition problems.

Face Detection Face Recognition +3

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

1 code implementation3 Nov 2016 Rajeev Ranjan, Swami Sankaranarayanan, Carlos D. Castillo, Rama Chellappa

The proposed method employs a multi-task learning framework that regularizes the shared parameters of CNN and builds a synergy among different domains and tasks.

Age Estimation Face Alignment +5

L2-constrained Softmax Loss for Discriminative Face Verification

1 code implementation28 Mar 2017 Rajeev Ranjan, Carlos D. Castillo, Rama Chellappa

In recent years, the performance of face verification systems has significantly improved using deep convolutional neural networks (DCNNs).

Face Verification

Improving Network Robustness against Adversarial Attacks with Compact Convolution

no code implementations3 Dec 2017 Rajeev Ranjan, Swami Sankaranarayanan, Carlos D. Castillo, Rama Chellappa

In particular, we show that learning features in a closed and bounded space improves the robustness of the network.

Face Verification

Crystal Loss and Quality Pooling for Unconstrained Face Verification and Recognition

no code implementations3 Apr 2018 Rajeev Ranjan, Ankan Bansal, Hongyu Xu, Swami Sankaranarayanan, Jun-Cheng Chen, Carlos D. Castillo, Rama Chellappa

We show that integrating this simple step in the training pipeline significantly improves the performance of face verification and recognition systems.

Face Verification

Deep Density Clustering of Unconstrained Faces

no code implementations CVPR 2018 Wei-An Lin, Jun-Cheng Chen, Carlos D. Castillo, Rama Chellappa

In this paper, we consider the problem of grouping a collection of unconstrained face images in which the number of subjects is not known.

Clustering

An Experimental Evaluation of Covariates Effects on Unconstrained Face Verification

no code implementations16 Aug 2018 Boyu Lu, Jun-Cheng Chen, Carlos D. Castillo, Rama Chellappa

In this paper, we comprehensively study two covariate related problems for unconstrained face verification: first, how covariates affect the performance of deep neural networks on the large-scale unconstrained face verification problem; second, how to utilize covariates to improve verification performance.

Face Recognition Face Verification

An Automatic System for Unconstrained Video-Based Face Recognition

no code implementations10 Dec 2018 Jingxiao Zheng, Rajeev Ranjan, Ching-Hui Chen, Jun-Cheng Chen, Carlos D. Castillo, Rama Chellappa

In this work, we consider challenging scenarios for unconstrained video-based face recognition from multiple-shot videos and surveillance videos with low-quality frames.

Face Recognition

On measuring the iconicity of a face

no code implementations4 Mar 2019 Prithviraj Dhar, Carlos D. Castillo, Rama Chellappa

For a given identity in a face dataset, there are certain iconic images which are more representative of the subject than others.

Face Verification

Uncertainty Modeling of Contextual-Connections between Tracklets for Unconstrained Video-based Face Recognition

no code implementations ICCV 2019 Jingxiao Zheng, Ruichi Yu, Jun-Cheng Chen, Boyu Lu, Carlos D. Castillo, Rama Chellappa

In this paper, we propose the Uncertainty-Gated Graph (UGG), which conducts graph-based identity propagation between tracklets, which are represented by nodes in a graph.

Face Recognition

How are attributes expressed in face DCNNs?

no code implementations12 Oct 2019 Prithviraj Dhar, Ankan Bansal, Carlos D. Castillo, Joshua Gleason, P. Jonathon Phillips, Rama Chellappa

In the final fully connected layer of the networks, we found the order of expressivity for facial attributes to be Age > Sex > Yaw.

Attribute

Accuracy comparison across face recognition algorithms: Where are we on measuring race bias?

no code implementations16 Dec 2019 Jacqueline G. Cavazos, P. Jonathon Phillips, Carlos D. Castillo, Alice J. O'Toole

We discuss data driven factors (e. g., image quality, image population statistics, and algorithm architecture), and scenario modeling factors that consider the role of the "user" of the algorithm (e. g., threshold decisions and demographic constraints).

Face Recognition

Towards Gender-Neutral Face Descriptors for Mitigating Bias in Face Recognition

no code implementations14 Jun 2020 Prithviraj Dhar, Joshua Gleason, Hossein Souri, Carlos D. Castillo, Rama Chellappa

Therefore, we present a novel `Adversarial Gender De-biasing algorithm (AGENDA)' to reduce the gender information present in face descriptors obtained from previously trained face recognition networks.

Attribute Face Recognition +2

A Synthesis-Based Approach for Thermal-to-Visible Face Verification

no code implementations21 Aug 2021 Neehar Peri, Joshua Gleason, Carlos D. Castillo, Thirimachos Bourlai, Vishal M. Patel, Rama Chellappa

Lastly, we show that our end-to-end thermal-to-visible face verification system provides strong performance on the MILAB-VTF(B) dataset.

Face Alignment Face Generation +1

Twin identification over viewpoint change: A deep convolutional neural network surpasses humans

no code implementations12 Jul 2022 Connor J. Parde, Virginia E. Strehle, Vivekjyoti Banerjee, Ying Hu, Jacqueline G. Cavazos, Carlos D. Castillo, Alice J. O'Toole

These findings also contribute to our understanding of DCNN performance for discriminating high-resemblance faces, demonstrate that the DCNN performs at a level at or above humans, and suggest a degree of parity between the features used by humans and the DCNN.

Face Identification

A Brief Survey on Person Recognition at a Distance

no code implementations17 Dec 2022 Chrisopher B. Nalty, Neehar Peri, Joshua Gleason, Carlos D. Castillo, Shuowen Hu, Thirimachos Bourlai, Rama Chellappa

Person recognition at a distance entails recognizing the identity of an individual appearing in images or videos collected by long-range imaging systems such as drones or surveillance cameras.

Face Verification Person Recognition +1

Recognizing People by Body Shape Using Deep Networks of Images and Words

no code implementations30 May 2023 Blake A. Myers, Lucas Jaggernauth, Thomas M. Metz, Matthew Q. Hill, Veda Nandan Gandi, Carlos D. Castillo, Alice J. O'Toole

Although the non-linguistic model yielded fewer false accepts at all distances, fusion of the linguistic and non-linguistic models decreased false accepts for all, but the UAV images.

Person Identification

SynCDR : Training Cross Domain Retrieval Models with Synthetic Data

1 code implementation31 Dec 2023 Samarth Mishra, Carlos D. Castillo, Hongcheng Wang, Kate Saenko, Venkatesh Saligrama

In cross-domain retrieval, a model is required to identify images from the same semantic category across two visual domains.

Retrieval Translation

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