Search Results for author:
Found 23 papers, 8 papers with code
Scale-aware competition network for palmprint recognition
This paper proposes a scale-aware competitive network (SAC-Net), which includes the Inner-Scale Competition Module (ISCM) and the Across-Scale Competition Module (ASCM) to capture texture characteristics related to orientation and scale.
Energizing Federated Learning via Filter-Aware Attention
Federated learning (FL) is a promising distributed paradigm, eliminating the need for data sharing but facing challenges from data heterogeneity.
Understanding the Feature Norm for Out-of-Distribution Detection
(3) The conventional feature norm fails to capture the deactivation tendency of hidden layer neurons, which may lead to misidentification of ID samples as OOD instances.
Nearest Neighbor Guidance for Out-of-Distribution Detection
Detecting out-of-distribution (OOD) samples are crucial for machine learning models deployed in open-world environments.
Ranked #1 on
Out-of-Distribution Detection
on ImageNet-1k vs Curated OODs (avg.)
(using extra training data)
Comprehensive Competition Mechanism in Palmprint Recognition
The traditional competition mechanism focuses solely on selecting the winner of different channels without considering the spatial information of the features.
Physics-Driven Spectrum-Consistent Federated Learning for Palmprint Verification
Subsequently, we introduce anchor models for short- and long-spectrum, which constrain the optimization directions of local models associated with long- and short-spectrum images.
Recognizability Embedding Enhancement for Very Low-Resolution Face Recognition and Quality Estimation
Very low-resolution face recognition (VLRFR) poses unique challenges, such as tiny regions of interest and poor resolution due to extreme standoff distance or wide viewing angle of the acquisition devices.
Open-Set Face Identification on Few-Shot Gallery by Fine-Tuning
In this paper, we focus on addressing the open-set face identification problem on a few-shot gallery by fine-tuning.
Gait-based Age Group Classification with Adaptive Graph Neural Network
This paper proposes a deep learning approach to extract age-associated features from model-based gait for age group classification.
Understanding Open-Set Recognition by Jacobian Norm and Inter-Class Separation
Overall, the discrepancy in the Jacobian norm between the known and unknown classes enables OSR.
Reconstruct Face from Features Using GAN Generator as a Distribution Constraint
Yet, the security and privacy of the extracted features from deep learning models (deep features) have been often overlooked.
3D-C2FT: Coarse-to-fine Transformer for Multi-view 3D Reconstruction
Recently, the transformer model has been successfully employed for the multi-view 3D reconstruction problem.
Abandoning the Bayer-Filter to See in the Dark
Next, a fully convolutional network is proposed to achieve the low-light image enhancement by fusing colored raw data with synthesized monochrome raw data.
Towards End-to-End Synthetic Speech Detection
The constant Q transform (CQT) has been shown to be one of the most effective speech signal pre-transforms to facilitate synthetic speech detection, followed by either hand-crafted (subband) constant Q cepstral coefficient (CQCC) feature extraction and a back-end binary classifier, or a deep neural network (DNN) directly for further feature extraction and classification.
Periocular Embedding Learning with Consistent Knowledge Distillation from Face
Overall, CKD empowers the sole periocular network to produce robust discriminative embeddings for periocular recognition in the wild.
Discriminative Multi-level Reconstruction under Compact Latent Space for One-Class Novelty Detection
In DCAE, (a) we force a compact latent space to bijectively represent the in-class data by reconstructing them through internal discriminative layers of generative adversarial nets.
On the Risk of Cancelable Biometrics
Cancelable biometrics (CB) employs an irreversible transformation to convert the biometric features into transformed templates while preserving the relative distance between two templates for security and privacy protection.
Periocular Recognition in the Wild with Orthogonal Combination of Local Binary Coded Pattern in Dual-stream Convolutional Neural Network
We also introduce and share a new dataset for periocular in the wild, namely Ethnic-ocular dataset for benchmarking.
A Symmetric Keyring Encryption Scheme for Biometric Cryptosystems
In this paper, we propose a novel biometric cryptosystem for vectorial biometrics named symmetric keyring encryption (SKE) inspired by Rivest's keyring model (2016).
Ranking Based Locality Sensitive Hashing Enabled Cancelable Biometrics: Index-of-Max Hashing
In this paper, we propose a ranking based locality sensitive hashing inspired two-factor cancelable biometrics, dubbed "Index-of-Max" (IoM) hashing for biometric template protection.
Rank Correlation Measure: A Representational Transformation for Biometric Template Protection
The former takes care of the accuracy performance mitigating numeric noises/perturbations while the latter offers strong non-invertible transformation via nonlinear feature embedding from Euclidean to Rank space that leads to toughness in inversion.
Multi-Fold Gabor, PCA and ICA Filter Convolution Descriptor for Face Recognition
The 2-FFC of Gabor, PCA and ICA filters thus yields three offspring sets: (1) Gabor filters solely, (2) Gabor-PCA filters, and (3) Gabor-ICA filters, to render the learning-free and the learning-based 2-FFC descriptors.
DCTNet : A Simple Learning-free Approach for Face Recognition
In this paper, we proposed a data-independence network, dubbed DCTNet for face recognition in which we adopt Discrete Cosine Transform (DCT) as filter banks in place of PCA.
