Search Results for author:
Found 38 papers, 14 papers with code
Camera-LiDAR Cross-modality Gait Recognition
In this work, we propose the first cross-modality gait recognition framework between Camera and LiDAR, namely CL-Gait.
Joint Identity Verification and Pose Alignment for Partial Fingerprints
Currently, portable electronic devices are becoming more and more popular.
Sports Analysis and VR Viewing System Based on Player Tracking and Pose Estimation with Multimodal and Multiview Sensors
The visualization results showcase the immense potential of our sports visualization system on the domain of watching games on VR/AR devices.
Latent Fingerprint Matching via Dense Minutia Descriptor
Latent fingerprint matching is a daunting task, primarily due to the poor quality of latent fingerprints.
Direct Regression of Distortion Field from a Single Fingerprint Image
However, existing rectification methods are based on principal component representation of distortion fields, which is not accurate and are very sensitive to finger pose.
Pose-Specific 3D Fingerprint Unfolding
The problem with this method is that there may be large elastic deformation between the unfolded rolled fingerprint and flat fingerprint, which affects the recognition rate.
Phase-aggregated Dual-branch Network for Efficient Fingerprint Dense Registration
Fingerprint dense registration aims to finely align fingerprint pairs at the pixel level, thereby reducing intra-class differences caused by distortion.
Regression of Dense Distortion Field from a Single Fingerprint Image
However, existing rectification methods are based on principal component representation of distortion fields, which is not accurate and are very sensitive to finger pose.
3D Vascular Segmentation Supervised by 2D Annotation of Maximum Intensity Projection
To alleviate this issue, we employ maximum intensity projection (MIP) to decrease the dimensionality of 3D volume to 2D image for efficient annotation, and the 2D labels are utilized to provide guidance and oversight for training 3D vessel segmentation model.
LiCamPose: Combining Multi-View LiDAR and RGB Cameras for Robust Single-frame 3D Human Pose Estimation
Several methods have been proposed to estimate 3D human pose from multi-view images, achieving satisfactory performance on public datasets collected under relatively simple conditions.
HumanReg: Self-supervised Non-rigid Registration of Human Point Cloud
In this paper, we present a novel registration framework, HumanReg, that learns a non-rigid transformation between two human point clouds end-to-end.
LiDAR-based Person Re-identification
Camera-based person re-identification (ReID) systems have been widely applied in the field of public security.
Fixed-length Dense Descriptor for Efficient Fingerprint Matching
In fingerprint matching, fixed-length descriptors generally offer greater efficiency compared to minutiae set, but the recognition accuracy is not as good as that of the latter.
LiDAR-HMR: 3D Human Mesh Recovery from LiDAR
In recent years, point cloud perception tasks have been garnering increasing attention.
Ranked #1 on
3D Human Pose Estimation
on SLOPER4D
Human-M3: A Multi-view Multi-modal Dataset for 3D Human Pose Estimation in Outdoor Scenes
In this article, we propose Human-M3, an outdoor multi-modal multi-view multi-person human pose database which includes not only multi-view RGB videos of outdoor scenes but also corresponding pointclouds.
A Flexible Multi-view Multi-modal Imaging System for Outdoor Scenes
The experimental results show that multi-view point clouds greatly improve 3D object detection and tracking accuracy regardless of complex and various outdoor environments.
Cerebrovascular Segmentation via Vessel Oriented Filtering Network
Accurate cerebrovascular segmentation from Magnetic Resonance Angiography (MRA) and Computed Tomography Angiography (CTA) is of great significance in diagnosis and treatment of cerebrovascular pathology.
Label2Label: A Language Modeling Framework for Multi-Attribute Learning
As each sample is annotated with multiple attribute labels, these "words" will naturally form an unordered but meaningful "sentence", which depicts the semantic information of the corresponding sample.
MetaAge: Meta-Learning Personalized Age Estimators
Unlike most existing personalized methods that learn the parameters of a personalized estimator for each person in the training set, our method learns the mapping from identity information to age estimator parameters.
Ranked #1 on
Age Estimation
on ChaLearn 2015
Monocular 3D Fingerprint Reconstruction and Unwarping
Compared with contact-based fingerprint acquisition techniques, contactless acquisition has the advantages of less skin distortion, larger fingerprint area, and hygienic acquisition.
Bridge-Prompt: Towards Ordinal Action Understanding in Instructional Videos
The generated text prompts are paired with corresponding video clips, and together co-train the text encoder and the video encoder via a contrastive approach.
Ranked #5 on
Action Segmentation
on GTEA
(using extra training data)
Reasoning Graph Networks for Kinship Verification: from Star-shaped to Hierarchical
To address this, we propose a Star-shaped Reasoning Graph Network (S-RGN).
Ranked #1 on
Kinship Verification
on KinFaceW-I
The Medical Segmentation Decathlon
Segmentation is so far the most widely investigated medical image processing task, but the various segmentation challenges have typically been organized in isolation, such that algorithm development was driven by the need to tackle a single specific clinical problem.
Meta-Mining Discriminative Samples for Kinship Verification
In the end, the samples in the unbalanced train batch are re-weighted by the learned meta-miner to optimize the kinship models.
Ranked #1 on
Kinship Verification
on KinFaceW-II
Learning Probabilistic Ordinal Embeddings for Uncertainty-Aware Regression
An ordinal distribution constraint is proposed to exploit the ordinal nature of regression.
Ranked #2 on
Age Estimation
on Adience
Aesthetics Quality Assessment
Age And Gender Classification
+3
GASNet: Weakly-supervised Framework for COVID-19 Lesion Segmentation
Segmentation of infected areas in chest CT volumes is of great significance for further diagnosis and treatment of COVID-19 patients.
Graph-Based Social Relation Reasoning
Human beings are fundamentally sociable -- that we generally organize our social lives in terms of relations with other people.
Ranked #1 on
Visual Social Relationship Recognition
on PIPA
Semantics-Driven Unsupervised Learning for Monocular Depth and Ego-Motion Estimation
In our method, we exploit semantic segmentation information to mitigate the effects of dynamic objects and occlusions in the scene, and to improve depth prediction performance by considering the correlation between depth and semantics.
Latent Fingerprint Registration via Matching Densely Sampled Points
Given a pair of fingerprints to match, we bypass the minutiae extraction step and take uniformly sampled points as key points.
Graph-based Kinship Reasoning Network
In this paper, we propose a graph-based kinship reasoning (GKR) network for kinship verification, which aims to effectively perform relational reasoning on the extracted features of an image pair.
Ranked #3 on
Kinship Verification
on KinFaceW-II
Dense Registration and Mosaicking of Fingerprints by Training an End-to-End Network
In addition, based on the proposed registration algorithm, we propose a fingerprint mosaicking method based on optimal seam selection.
BridgeNet: A Continuity-Aware Probabilistic Network for Age Estimation
Existing methods for age estimation usually apply a divide-and-conquer strategy to deal with heterogeneous data caused by the non-stationary aging process.
Ranked #2 on
Age Estimation
on FGNET
CFUN: Combining Faster R-CNN and U-net Network for Efficient Whole Heart Segmentation
In this paper, we propose a novel heart segmentation pipeline Combining Faster R-CNN and U-net Network (CFUN).
Consistent-Aware Deep Learning for Person Re-Identification in a Camera Network
In this paper, we propose a consistent-aware deep learning (CADL) framework for person re-identification in a camera network.
Learning Deep Binary Descriptor With Multi-Quantization
In this paper, we propose an unsupervised feature learning method called deep binary descriptor with multi-quantization (DBD-MQ) for visual matching.
Correlated and Individual Multi-Modal Deep Learning for RGB-D Object Recognition
Specifically, we construct a pair of deep convolutional neural networks (CNNs) for the RGB and depth data, and concatenate them at the top layer of the network with a loss function which learns a new feature space where both correlated part and the individual part of the RGB-D information are well modelled.
Multiple Feature Fusion via Weighted Entropy for Visual Tracking
It is desirable to combine multiple feature descriptors to improve the visual tracking performance because different features can provide complementary information to describe objects of interest.
Smooth Representation Clustering
Based on our analysis, we propose the SMooth Representation (SMR) model.
