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Found 39 papers, 14 papers with code
Exploring ChatGPT for Face Presentation Attack Detection in Zero and Few-Shot in-Context Learning
This study highlights the potential of ChatGPT (specifically GPT-4o) as a competitive alternative for Face Presentation Attack Detection (PAD), outperforming several PAD models, including commercial solutions, in specific scenarios.
Second FRCSyn-onGoing: Winning Solutions and Post-Challenge Analysis to Improve Face Recognition with Synthetic Data
In order to promote the proposal of novel Generative AI methods and synthetic data, and investigate the application of synthetic data to better train face recognition systems, we introduce the 2nd FRCSyn-onGoing challenge, based on the 2nd Face Recognition Challenge in the Era of Synthetic Data (FRCSyn), originally launched at CVPR 2024.
Face Reconstruction from Face Embeddings using Adapter to a Face Foundation Model
The generated images are evaluated on different face recognition models and different datasets, demonstrating the effectiveness of our method to translate embeddings of different face recognition models.
Digi2Real: Bridging the Realism Gap in Synthetic Data Face Recognition via Foundation Models
Yet, such models still rely on real data to train the generative models and generally exhibit inferior performance compared to those trained on real datasets.
Modality Agnostic Heterogeneous Face Recognition with Switch Style Modulators
Heterogeneous Face Recognition (HFR) systems aim to enhance the capability of face recognition in challenging cross-modal authentication scenarios.
From Modalities to Styles: Rethinking the Domain Gap in Heterogeneous Face Recognition
In our work, we view different modalities as distinct styles and propose a method to modulate feature maps of the target modality to address the domain gap.
Heterogeneous Face Recognition Using Domain Invariant Units
Heterogeneous Face Recognition (HFR) aims to expand the applicability of Face Recognition (FR) systems to challenging scenarios, enabling the matching of face images across different domains, such as matching thermal images to visible spectra.
Second Edition FRCSyn Challenge at CVPR 2024: Face Recognition Challenge in the Era of Synthetic Data
Synthetic data is gaining increasing relevance for training machine learning models.
SDFR: Synthetic Data for Face Recognition Competition
The submitted models were trained on existing and also new synthetic datasets and used clever methods to improve training with synthetic data.
Model Pairing Using Embedding Translation for Backdoor Attack Detection on Open-Set Classification Tasks
In this paper we propose to use model pairs on open-set classification tasks for detecting backdoors.
FRCSyn Challenge at WACV 2024:Face Recognition Challenge in the Era of Synthetic Data
Despite the widespread adoption of face recognition technology around the world, and its remarkable performance on current benchmarks, there are still several challenges that must be covered in more detail.
SynthDistill: Face Recognition with Knowledge Distillation from Synthetic Data
While generating synthetic datasets for training face recognition models is an alternative option, it is challenging to generate synthetic data with sufficient intra-class variations.
Ranked #1 on
Synthetic Face Recognition
on AgeDB-30
(Accuracy metric)
EFaR 2023: Efficient Face Recognition Competition
To drive further development of efficient face recognition models, the submitted solutions are ranked based on a weighted score of the achieved verification accuracies on a diverse set of benchmarks, as well as the deployability given by the number of floating-point operations and model size.
Bridging the Gap: Heterogeneous Face Recognition with Conditional Adaptive Instance Modulation
Heterogeneous Face Recognition (HFR) aims to match face images across different domains, such as thermal and visible spectra, expanding the applicability of Face Recognition (FR) systems to challenging scenarios.
EdgeFace: Efficient Face Recognition Model for Edge Devices
In this paper, we present EdgeFace, a lightweight and efficient face recognition network inspired by the hybrid architecture of EdgeNeXt.
Ranked #1 on
Lightweight Face Recognition
on CFP-FP
Prepended Domain Transformer: Heterogeneous Face Recognition without Bells and Whistles
The core idea of the proposed approach is to add a novel neural network block called Prepended Domain Transformer (PDT) in front of a pre-trained face recognition (FR) model to address the domain gap.
A Comprehensive Evaluation on Multi-channel Biometric Face Presentation Attack Detection
Having a lot of sensors increases the cost of the system, and therefore an understanding of the performance of different sensors against a wide variety of attacks is necessary while selecting the modalities.
Cross Modal Focal Loss for RGBD Face Anti-Spoofing
Automatic methods for detecting presentation attacks are essential to ensure the reliable use of facial recognition technology.
On the Effectiveness of Vision Transformers for Zero-shot Face Anti-Spoofing
Although various methods have been suggested for detecting such attacks, most of them over-fit the training set and fail in generalizing to unseen attacks and environments.
The High-Quality Wide Multi-Channel Attack (HQ-WMCA) database
The High-Quality Wide Multi-Channel Attack database (HQ-WMCA) database extends the previous Wide Multi-Channel Attack database(WMCA), with more channels including color, depth, thermal, infrared (spectra), and short-wave infrared (spectra), and also a wide variety of attacks.
Deep Models and Shortwave Infrared Information to Detect Face Presentation Attacks
Conducted experiments show superior performance over similar models acting on either color images or on a combination of different modalities (visible, NIR, thermal and depth), as well as on a SVM-based classifier acting on SWIR image differences.
Learning One Class Representations for Face Presentation Attack Detection using Multi-channel Convolutional Neural Networks
The proposed system is evaluated on the publicly available WMCA multi-channel face PAD database, which contains a wide variety of 2D and 3D attacks.
Ranked #1 on
Face Anti-Spoofing
on MLFP
Can Your Face Detector Do Anti-spoofing? Face Presentation Attack Detection with a Multi-Channel Face Detector
In a typical face recognition pipeline, the task of the face detector is to localize the face region.
Ranked #1 on
Face Presentation Attack Detection
on WMCA
(ACER@0.2BPCER metric)
Biometric Face Presentation Attack Detection with Multi-Channel Convolutional Neural Network
We also introduce the new Wide Multi-Channel presentation Attack (WMCA) database for face PAD which contains a wide variety of 2D and 3D presentation attacks for both impersonation and obfuscation attacks.
Ranked #2 on
Face Presentation Attack Detection
on WMCA
Image based Eye Gaze Tracking and its Applications
In the second part of this work, we have developed two applications which can benefit from eye tracking data.
Domain Adaptation in Multi-Channel Autoencoder based Features for Robust Face Anti-Spoofing
The proposed system is tested on a very recent publicly available multi-channel PAD database with a wide variety of presentation attacks.
Deep Pixel-wise Binary Supervision for Face Presentation Attack Detection
The proposed approach achieves an HTER of 0% in Replay Mobile dataset and an ACER of 0. 42% in Protocol-1 of OULU dataset outperforming state of the art methods.
ESCaF: Pupil Centre Localization Algorithm with Candidate Filtering
A simple tracking scheme has also been added which improves the processing speed.
Recognition of Activities from Eye Gaze and Egocentric Video
This paper presents a framework for recognition of human activity from egocentric video and eye tracking data obtained from a head-mounted eye tracker.
The Unconstrained Ear Recognition Challenge
In this paper we present the results of the Unconstrained Ear Recognition Challenge (UERC), a group benchmarking effort centered around the problem of person recognition from ear images captured in uncontrolled conditions.
Real-time Eye Gaze Direction Classification Using Convolutional Neural Network
We propose a real-time framework for the classification of eye gaze direction and estimation of eye accessing cues.
Fast and Accurate Algorithm for Eye Localization for Gaze Tracking in Low Resolution Images
A two-stage algorithm is proposed for iris centre localization.
A Score-level Fusion Method for Eye Movement Biometrics
Features extracted from fixations and saccades are used by a Gaussian Radial Basis Function Network (GRBFN) based method for biometric authentication.
Ranked #1 on
Person Identification
on BioEye
An Improved Algorithm for Eye Corner Detection
In this paper, a modified algorithm for the detection of nasal and temporal eye corners is presented.
Design and Implementation of Real-time Algorithms for Eye Tracking and PERCLOS Measurement for on board Estimation of Alertness of Drivers
Local Binary Pattern (LBP) histogram based method is used for the detection of eyes at night time.
A Real Time Facial Expression Classification System Using Local Binary Patterns
A customizable approach is proposed for facial expression analysis, since the various expressions and intensity of expressions vary from person to person.
A Vision Based System for Monitoring the Loss of Attention in Automotive Drivers
In this paper, we propose a robust real time embedded platform to monitor the loss of attention of the driver during day as well as night driving conditions.
A Framework for Fast Face and Eye Detection
Face detection is an essential step in many computer vision applications like surveillance, tracking, medical analysis, facial expression analysis etc.
