Search Results for author:
Found 18 papers, 9 papers with code
Enhancement-Driven Pretraining for Robust Fingerprint Representation Learning
Fingerprint recognition stands as a pivotal component of biometric technology, with diverse applications from identity verification to advanced search tools.
Finger-UNet: A U-Net based Multi-Task Architecture for Deep Fingerprint Enhancement
Furthermore, we also integrate the orientation estimation task to propagate the knowledge of ridge orientations to enhance the performance further.
Face Cartoonisation For Various Poses Using StyleGAN
This paper presents an innovative approach to achieve face cartoonisation while preserving the original identity and accommodating various poses.
Transformer based Fingerprint Feature Extraction
Our convolutional transformer based approach with an in-built minutiae extractor provides a time and memory efficient solution to extract a global as well as a local representation of the fingerprint.
A Unified Model for Fingerprint Authentication and Presentation Attack Detection
Therefore, rather than performing the two tasks separately, we propose a joint model for spoof detection and matching to simultaneously perform both tasks without compromising the accuracy of either task.
Reducing the Variance of Variational Estimates of Mutual Information by Limiting the Critic's Hypothesis Space to RKHS
We argue that the high variance characteristic is due to the uncontrolled complexity of the critic's hypothesis space.
Mutual Information Based Method for Unsupervised Disentanglement of Video Representation
In this work, we propose Mutual Information Predictive Auto-Encoder (MIPAE) framework, that reduces the task of predicting high dimensional video frames by factorising video representations into content and low dimensional pose latent variables that are easy to predict.
Understanding Dynamic Scenes using Graph Convolution Networks
We present a novel Multi-Relational Graph Convolutional Network (MRGCN) based framework to model on-road vehicle behaviors from a sequence of temporally ordered frames as grabbed by a moving monocular camera.
Ranked #1 on
Test results
on KITTI
Towards Accurate Vehicle Behaviour Classification With Multi-Relational Graph Convolutional Networks
Understanding on-road vehicle behaviour from a temporal sequence of sensor data is gaining in popularity.
CineFilter: Unsupervised Filtering for Real Time Autonomous Camera Systems
Autonomous camera systems are often subjected to an optimization/filtering operation to smoothen and stabilize the rough trajectory estimates.
Universal Material Translator: Towards Spoof Fingerprint Generalization
Spoof detectors are classifiers that are trained to distinguish spoof fingerprints from bonafide ones.
IDD: A Dataset for Exploring Problems of Autonomous Navigation in Unconstrained Environments
It also reflects label distributions of road scenes significantly different from existing datasets, with most classes displaying greater within-class diversity.
Hybrid Binary Networks: Optimizing for Accuracy, Efficiency and Memory
We analyze the binarization tradeoff using a metric that jointly models the input binarization-error and computational cost and introduce an efficient algorithm to select layers whose inputs are to be binarized.
Distribution-Aware Binarization of Neural Networks for Sketch Recognition
We present a theoretical analysis of the technique to show the effective representational power of the resulting layers, and explore the forms of data they model best.
Semi-Adversarial Networks: Convolutional Autoencoders for Imparting Privacy to Face Images
In this paper, we design and evaluate a convolutional autoencoder that perturbs an input face image to impart privacy to a subject.
Deep Expander Networks: Efficient Deep Networks from Graph Theory
Inspired by these techniques, we propose to model connections between filters of a CNN using graphs which are simultaneously sparse and well connected.
Pose-Aware Person Recognition
Person recognition methods that use multiple body regions have shown significant improvements over traditional face-based recognition.
Visual Phrases for Exemplar Face Detection
Contrary to traditional approaches that model face variations from a large and diverse set of training examples, exemplar-based approaches use a collection of discriminatively trained exemplars for detection.
