On RGB-D face recognition using Kinect
- Gaurav Goswami, Samarth Bharadwaj, Mayank Vatsa, Richa Singh
- Computer ScienceInternational Conference on Biometrics: Theory…
- 1 September 2013
The experimental results indicate that the RGB-D information obtained by Kinect can be used to achieve improved face recognition performance compared to existing 2D and 3D approaches.
Recognizing composite sketches with digital face images via SSD dictionary
- Paritosh Mittal, Aishwarya Jain, Gaurav Goswami, Richa Singh, Mayank Vatsa
- Computer ScienceIEEE International Joint Conference on Biometrics
- 29 December 2014
The proposed algorithm utilizes a SSD based dictionary generated via 50,000 images from the CMU Multi-PIE database, and the gallery-probe feature vectors created using SSD dictionary are matched using GentleBoostKO classifier.
RGB-D Face Recognition With Texture and Attribute Features
- Gaurav Goswami, Mayank Vatsa, Richa Singh
- Computer ScienceIEEE Transactions on Information Forensics and…
- 1 October 2014
The experimental results indicate that the proposed algorithm achieves high face recognition accuracy on RGB-D images obtained using Kinect compared with existing 2D and 3D approaches.
FaceDCAPTCHA: Face detection based color image CAPTCHA
- Gaurav Goswami, Brian M. Powell, Mayank Vatsa, Richa Singh, A. Noore
- Computer ScienceFuture generations computer systems
- 1 February 2014
FR-CAPTCHA: CAPTCHA Based on Recognizing Human Faces
- Gaurav Goswami, Brian M. Powell, Mayank Vatsa, Richa Singh, A. Noore
- Computer SciencePLoS ONE
- 15 April 2014
This work proposes FR-CAPTCHA, a Turing test based on finding matching pairs of human faces in an image which achieves a human accuracy of 94% and is robust against automated attacks.
Detecting and Mitigating Adversarial Perturbations for Robust Face Recognition
- Gaurav Goswami, Akshay Agarwal, N. Ratha, Richa Singh, Mayank Vatsa
- Computer ScienceInternational Journal of Computer Vision
- 22 March 2019
This paper attempts to unravel three aspects related to the robustness of DNNs for face recognition in terms of vulnerabilities to attacks, detecting the singularities by characterizing abnormal filter response behavior in the hidden layers of deep networks; and making corrections to the processing pipeline to alleviate the problem.
Face Verification via Learned Representation on Feature-Rich Video Frames
- Gaurav Goswami, Mayank Vatsa, Richa Singh
- Computer ScienceIEEE Transactions on Information Forensics and…
- 1 July 2017
Experimental analysis suggests that the proposed feature-richness-based frame selection offers noticeable and consistent performance improvement compared with frontal only frames, random frames, or frame selection using perceptual no-reference image quality measures and joint feature learning in SDAE and sparse and low rank regularization in DBM helps in improving face verification performance.
MDLFace: Memorability augmented deep learning for video face recognition
- Gaurav Goswami, Romil Bhardwaj, Richa Singh, Mayank Vatsa
- Computer ScienceIEEE International Joint Conference on Biometrics
- 29 December 2014
A memorability based frame selection algorithm is presented that enables automatic selection of memorable frames for facial feature extraction and matching and achieves state-of-the-art performance at low false accept rates.
Unravelling Robustness of Deep Learning based Face Recognition Against Adversarial Attacks
- Gaurav Goswami, N. Ratha, Akshay Agarwal, Richa Singh, Mayank Vatsa
- Computer ScienceAAAI Conference on Artificial Intelligence
- 1 February 2018
This paper attempts to unravel three aspects related to the robustness of DNNs for face recognition in terms of vulnerabilities to attacks inspired by commonly observed distortions in the real world, and presents several effective countermeasures to mitigate the impact of adversarial attacks and improve the overall robustnessof DNN-based face recognition.
Group sparse representation based classification for multi-feature multimodal biometrics
- Gaurav Goswami, Paritosh Mittal, A. Majumdar, Mayank Vatsa, Richa Singh
- Computer ScienceInformation Fusion
- 1 November 2016
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