Search Results for author:
Found 89 papers, 26 papers with code
Beyond 3DMM Space: Towards Fine-grained 3D Face Reconstruction
However, most of their training data is constructed by 3D Morphable Model, whose space spanned is only a small part of the shape space.
Exclusivity-Consistency Regularized Knowledge Distillation for Face Recognition
Knowledge distillation is an effective tool to compress large pre-trained Convolutional Neural Networks (CNNs) or their ensembles into models applicable to mobile and embedded devices.
OTAvatar: One-shot Talking Face Avatar with Controllable Tri-plane Rendering
In this paper, we propose One-shot Talking face Avatar (OTAvatar), which constructs face avatars by a generalized controllable tri-plane rendering solution so that each personalized avatar can be constructed from only one portrait as the reference.
Graphics Capsule: Learning Hierarchical 3D Face Representations from 2D Images
The function of constructing the hierarchy of objects is important to the visual process of the human brain.
Sharpness-Aware Gradient Matching for Domain Generalization
In this paper, we present two conditions to ensure that the model could converge to a flat minimum with a small loss, and present an algorithm, named Sharpness-Aware Gradient Matching (SAGM), to meet the two conditions for improving model generalization capability.
Intrinsic Physical Concepts Discovery with Object-Centric Predictive Models
The ability to discover abstract physical concepts and understand how they work in the world through observing lies at the core of human intelligence.
Self-similarity Driven Scale-invariant Learning for Weakly Supervised Person Search
On the other hand, the similarity of cross-scale images is often smaller than that of images with the same scale for a person, which will increase the difficulty of matching.
Deep Learning for Human Parsing: A Survey
Human parsing is a key topic in image processing with many applications, such as surveillance analysis, human-robot interaction, person search, and clothing category classification, among many others.
Surveillance Face Anti-spoofing
In order to promote relevant research and fill this gap in the community, we collect a large-scale Surveillance High-Fidelity Mask (SuHiFiMask) dataset captured under 40 surveillance scenes, which has 101 subjects from different age groups with 232 3D attacks (high-fidelity masks), 200 2D attacks (posters, portraits, and screens), and 2 adversarial attacks.
Face Presentation Attack Detection
Face recognition technology has been widely used in daily interactive applications such as checking-in and mobile payment due to its convenience and high accuracy.
DFGC 2022: The Second DeepFake Game Competition
There is a two-party game between DeepFake creators and defenders.
Single-Image 3D Face Reconstruction under Perspective Projection
In 3D face reconstruction, orthogonal projection has been widely employed to substitute perspective projection to simplify the fitting process.
MVP-Human Dataset for 3D Human Avatar Reconstruction from Unconstrained Frames
In this paper, we consider a novel problem of reconstructing a 3D human avatar from multiple unconstrained frames, independent of assumptions on camera calibration, capture space, and constrained actions.
Weakly Aligned Feature Fusion for Multimodal Object Detection
In this article, we propose a general multimodal detector named aligned region CNN (AR-CNN) to tackle the position shift problem.
Beyond 3DMM: Learning to Capture High-fidelity 3D Face Shape
3D Morphable Model (3DMM) fitting has widely benefited face analysis due to its strong 3D priori.
Nested Collaborative Learning for Long-Tailed Visual Recognition
NCL consists of two core components, namely Nested Individual Learning (NIL) and Nested Balanced Online Distillation (NBOD), which focus on the individual supervised learning for each single expert and the knowledge transferring among multiple experts, respectively.
Ranked #2 on
Long-tail Learning
on CIFAR-10-LT (ρ=50)
HP-Capsule: Unsupervised Face Part Discovery by Hierarchical Parsing Capsule Network
Capsule networks are designed to present the objects by a set of parts and their relationships, which provide an insight into the procedure of visual perception.
Solving parametric partial differential equations with deep rectified quadratic unit neural networks
In this study, we investigate the expressive power of deep rectified quadratic unit (ReQU) neural networks for approximating the solution maps of parametric PDEs.
VLAD-VSA: Cross-Domain Face Presentation Attack Detection with Vocabulary Separation and Adaptation
In this paper, the VLAD aggregation method is adopted to quantize local features with visual vocabulary locally partitioning the feature space, and hence preserve the local discriminability.
Multi-initialization Optimization Network for Accurate 3D Human Pose and Shape Estimation
In the second stage, we design a mesh refinement transformer (MRT) to respectively refine each coarse reconstruction result via a self-attention mechanism.
Ranked #26 on
3D Human Pose Estimation
on 3DPW
(MPJPE metric)
Decoupling and Recoupling Spatiotemporal Representation for RGB-D-based Motion Recognition
Decoupling spatiotemporal representation refers to decomposing the spatial and temporal features into dimension-independent factors.
Consistency Regularization for Deep Face Anti-Spoofing
Face anti-spoofing (FAS) plays a crucial role in securing face recognition systems.
Meta-Teacher For Face Anti-Spoofing
The meta-teacher is trained in a bi-level optimization manner to learn the ability to supervise the PA detectors learning rich spoofing cues.
LAE : Long-tailed Age Estimation
To improve the performance of facial age estimation, we first formulate a simple standard baseline and build a much strong one by collecting the tricks in pre-training, data augmentation, model architecture, and so on.
OBJECT DYNAMICS DISTILLATION FOR SCENE DECOMPOSITION AND REPRESENTATION
In this paper, we work on object dynamics and propose Object Dynamics Distillation Network (ODDN), a framework that distillates explicit object dynamics (e. g., velocity) from sequential static representations.
3D High-Fidelity Mask Face Presentation Attack Detection Challenge
The threat of 3D masks to face recognition systems is increasingly serious and has been widely concerned by researchers.
PoseFace: Pose-Invariant Features and Pose-Adaptive Loss for Face Recognition
Despite the great success achieved by deep learning methods in face recognition, severe performance drops are observed for large pose variations in unconstrained environments (e. g., in cases of surveillance and photo-tagging).
Deep Learning for Face Anti-Spoofing: A Survey
Face anti-spoofing (FAS) has lately attracted increasing attention due to its vital role in securing face recognition systems from presentation attacks (PAs).
Represent Items by Items: An Enhanced Representation of the Target Item for Recommendation
Our proposed Co-occurrence based Enhanced Representation model (CER) learns the scoring function by a deep neural network with the attentive user representation and fusion of raw representation and enhanced representation of target item as input.
Contrastive Context-Aware Learning for 3D High-Fidelity Mask Face Presentation Attack Detection
To bridge the gap to real-world applications, we introduce a largescale High-Fidelity Mask dataset, namely CASIA-SURF HiFiMask (briefly HiFiMask).
Searching for Alignment in Face Recognition
A standard pipeline of current face recognition frameworks consists of four individual steps: locating a face with a rough bounding box and several fiducial landmarks, aligning the face image using a pre-defined template, extracting representations and comparing.
Face Forgery Detection by 3D Decomposition
Detecting digital face manipulation has attracted extensive attention due to fake media's potential harms to the public.
Towards Fast, Accurate and Stable 3D Dense Face Alignment
Firstly, on the basis of a lightweight backbone, we propose a meta-joint optimization strategy to dynamically regress a small set of 3DMM parameters, which greatly enhances speed and accuracy simultaneously.
Ranked #1 on
3D Face Reconstruction
on Florence
(Mean NME metric)
SADet: Learning An Efficient and Accurate Pedestrian Detector
Although the anchor-based detectors have taken a big step forward in pedestrian detection, the overall performance of algorithm still needs further improvement for practical applications, \emph{e. g.}, a good trade-off between the accuracy and efficiency.
NPCFace: Negative-Positive Collaborative Training for Large-scale Face Recognition
However, the correlation between hard positive and hard negative is overlooked, and so is the relation between the margins in positive and negative logits.
Semi-Siamese Training for Shallow Face Learning
Extensive experiments on various benchmarks of face recognition show the proposed method significantly improves the training, not only in shallow face learning, but also for conventional deep face data.
Multi-Modal Face Anti-Spoofing Based on Central Difference Networks
Face anti-spoofing (FAS) plays a vital role in securing face recognition systems from presentation attacks.
Domain Balancing: Face Recognition on Long-Tailed Domains
Finally, we propose a Domain Balancing Margin (DBM) in the loss function to further optimize the feature space of the tail domains to improve generalization.
Deep Spatial Gradient and Temporal Depth Learning for Face Anti-spoofing
Depth supervised learning has been proven as one of the most effective methods for face anti-spoofing.
Learning Meta Face Recognition in Unseen Domains
Face recognition systems are usually faced with unseen domains in real-world applications and show unsatisfactory performance due to their poor generalization.
LAMP-HQ: A Large-Scale Multi-Pose High-Quality Database and Benchmark for NIR-VIS Face Recognition
A spectral conditional attention module is introduced to reduce the domain gap between NIR and VIS data and then improve the performance of NIR-VIS heterogeneous face recognition on various databases including the LAMP-HQ.
Bridging the Gap Between Anchor-based and Anchor-free Detection via Adaptive Training Sample Selection
In this paper, we first point out that the essential difference between anchor-based and anchor-free detection is actually how to define positive and negative training samples, which leads to the performance gap between them.
Ranked #80 on
Object Detection
on COCO test-dev
Relational Learning for Joint Head and Human Detection
Head and human detection have been rapidly improved with the development of deep convolutional neural networks.
PedHunter: Occlusion Robust Pedestrian Detector in Crowded Scenes
Pedestrian detection in crowded scenes is a challenging problem, because occlusion happens frequently among different pedestrians.
RefineFace: Refinement Neural Network for High Performance Face Detection
To improve the classification ability for high recall efficiency, STC first filters out most simple negatives from low level detection layers to reduce search space for subsequent classifier, then SML is applied to better distinguish faces from background at various scales and FSM is introduced to let the backbone learn more discriminative features for classification.
Domain Adaptive Person Re-Identification via Camera Style Generation and Label Propagation
We derive a camera style adaptation framework to learn the style-based mappings between different camera views, from the target domain to the source domain, and then we can transfer the identity-based distribution from the source domain to the target domain on the camera level.
Domain Adaptive Person Re-Identification
Person Re-Identification
+1
Learning Meta Model for Zero- and Few-shot Face Anti-spoofing
Therefore, we define face anti-spoofing as a zero- and few-shot learning problem.
Semantic Alignment: Finding Semantically Consistent Ground-truth for Facial Landmark Detection
Despite this, we notice that the semantic ambiguity greatly degrades the detection performance.
Ranked #1 on
Face Alignment
on 300W
(NME_inter-pupil (%, Full) metric)
WIDER Face and Pedestrian Challenge 2018: Methods and Results
This paper presents a review of the 2018 WIDER Challenge on Face and Pedestrian.
Weakly Aligned Cross-Modal Learning for Multispectral Pedestrian Detection
In this paper, we propose a novel Aligned Region CNN (AR-CNN) to handle the weakly aligned multispectral data in an end-to-end way.
Improving Face Anti-Spoofing by 3D Virtual Synthesis
Specifically, we consider a printed photo as a flat surface and mesh it into a 3D object, which is then randomly bent and rotated in 3D space.
Ranked #1 on
Face Anti-Spoofing
on CASIA-MFSD
Recurrent Calibration Network for Irregular Text Recognition
In this paper, we propose a novel Recurrent Calibration Network (RCN) for irregular scene text recognition.
Prior-Knowledge and Attention-based Meta-Learning for Few-Shot Learning
In this paper, inspired by the human cognition process which utilizes both prior-knowledge and vision attention in learning new knowledge, we present a novel paradigm of meta-learning approach with three developments to introduce attention mechanism and prior-knowledge for meta-learning.
Representation based and Attention augmented Meta learning
The method RAML aims to give the Meta learner the ability of leveraging the past learned knowledge to reduce the dimension of the original input data by expressing it into high representations, and help the Meta learner to perform well.
Exploiting temporal and depth information for multi-frame face anti-spoofing
Face anti-spoofing is significant to the security of face recognition systems.
Vehicle Re-identification Using Quadruple Directional Deep Learning Features
Specifically, the same basic deep learning architecture is a shortly and densely connected convolutional neural network to extract basic feature maps of an input square vehicle image in the first stage.
Ranked #3 on
Vehicle Re-Identification
on VehicleID Large
(mAP metric)
Selective Refinement Network for High Performance Face Detection
In particular, the SRN consists of two modules: the Selective Two-step Classification (STC) module and the Selective Two-step Regression (STR) module.
Ranked #1 on
Face Detection
on PASCAL Face
Occlusion-aware R-CNN: Detecting Pedestrians in a Crowd
Pedestrian detection in crowded scenes is a challenging problem since the pedestrians often gather together and occlude each other.
Ranked #8 on
Pedestrian Detection
on Caltech
(using extra training data)
Large-scale Bisample Learning on ID Versus Spot Face Recognition
In this paper, we propose a deep learning based large-scale bisample learning (LBL) method for IvS face recognition.
Face Synthesis for Eyeglass-Robust Face Recognition
A feasible method is to collect large-scale face images with eyeglasses for training deep learning methods.
Ensemble Soft-Margin Softmax Loss for Image Classification
On the other hand, the learned classifier of softmax loss is weak.
Face Alignment in Full Pose Range: A 3D Total Solution
In this paper, we propose to tackle these three challenges in an new alignment framework termed 3D Dense Face Alignment (3DDFA), in which a dense 3D Morphable Model (3DMM) is fitted to the image via Cascaded Convolutional Neural Networks.
Ranked #3 on
Face Alignment
on AFLW
Single-Shot Refinement Neural Network for Object Detection
For object detection, the two-stage approach (e. g., Faster R-CNN) has been achieving the highest accuracy, whereas the one-stage approach (e. g., SSD) has the advantage of high efficiency.
Ranked #42 on
Object Detection
on COCO test-dev
S3FD: Single Shot Scale-Invariant Face Detector
This paper presents a real-time face detector, named Single Shot Scale-invariant Face Detector (S3FD), which performs superiorly on various scales of faces with a single deep neural network, especially for small faces.
FaceBoxes: A CPU Real-time Face Detector with High Accuracy
The MSCL aims at enriching the receptive fields and discretizing anchors over different layers to handle faces of various scales.
Ranked #3 on
Face Detection
on PASCAL Face
S$^3$FD: Single Shot Scale-invariant Face Detector
This paper presents a real-time face detector, named Single Shot Scale-invariant Face Detector (S$^3$FD), which performs superiorly on various scales of faces with a single deep neural network, especially for small faces.
Ranked #2 on
Face Detection
on PASCAL Face
Learning Efficient Image Representation for Person Re-Identification
Then, a robust image representation based on color names is obtained by concatenating the statistical descriptors in each stripe.
Exclusivity-Consistency Regularized Multi-View Subspace Clustering
Multi-view subspace clustering aims to partition a set of multi-source data into their underlying groups.
Deep Hybrid Similarity Learning for Person Re-identification
In this paper, a deep hybrid similarity learning (DHSL) method for person Re-ID based on a convolution neural network (CNN) is proposed.
Embedding Deep Metric for Person Re-identication A Study Against Large Variations
From this point of view, selecting suitable positive i. e. intra-class) training samples within a local range is critical for training the CNN embedding, especially when the data has large intra-class variations.
Learning Discriminative Features with Class Encoder
Deep neural networks usually benefit from unsupervised pre-training, e. g. auto-encoders.
CRAFT Objects from Images
They decompose the object detection problem into two cascaded easier tasks: 1) generating object proposals from images, 2) classifying proposals into various object categories.
Constrained Deep Metric Learning for Person Re-identification
In this paper, we propose a novel CNN-based method to learn a discriminative metric with good robustness to the over-fitting problem in person re-identification.
Face Alignment Across Large Poses: A 3D Solution
Face alignment, which fits a face model to an image and extracts the semantic meanings of facial pixels, has been an important topic in CV community.
Ranked #3 on
3D Face Reconstruction
on Florence
UA-DETRAC: A New Benchmark and Protocol for Multi-Object Detection and Tracking
In this work, we perform a comprehensive quantitative study on the effects of object detection accuracy to the overall MOT performance, using the new large-scale University at Albany DETection and tRACking (UA-DETRAC) benchmark dataset.
Object Detection by Labeling Superpixels
Object detection is always conducted by object proposal generation and classification sequentially.
JOTS: Joint Online Tracking and Segmentation
We present a novel Joint Online Tracking and Segmentation (JOTS) algorithm which integrates the multi-part tracking and segmentation into a unified energy optimization framework to handle the video segmentation task.
High-Fidelity Pose and Expression Normalization for Face Recognition in the Wild
Pose and expression normalization is a crucial step to recover the canonical view of faces under arbitrary conditions, so as to improve the face recognition performance.
Convolutional Channel Features
With the combination of CNN features and boosting forest, CCF benefits from the richer capacity in feature representation compared with channel features, as well as lower cost in computation and storage compared with end-to-end CNN methods.
Learning Face Representation from Scratch
The current situation in the field of face recognition is that data is more important than algorithm.
Learn Convolutional Neural Network for Face Anti-Spoofing
Moreover, the nets trained using combined data from two datasets have less biases between two datasets.
Ranked #2 on
Face Anti-Spoofing
on CASIA-MFSD
Deep Metric Learning for Practical Person Re-Identification
Compared to existing researches, a more practical setting is studied in the experiments that is training and test on different datasets (cross dataset person re-identification).
Aggregate channel features for multi-view face detection
Face detection has drawn much attention in recent decades since the seminal work by Viola and Jones.
Ranked #29 on
Face Detection
on WIDER Face (Medium)
Shared Representation Learning for Heterogeneous Face Recognition
For NIR-VIS problem, we produce new state-of-the-art performance on the CASIA HFB and NIR-VIS 2. 0 databases.
The Fastest Deformable Part Model for Object Detection
Three prohibitive steps in cascade version of DPM are accelerated, including 2D correlation between root filter and feature map, cascade part pruning and HOG feature extraction.
Multiple Target Tracking Based on Undirected Hierarchical Relation Hypergraph
Multi-target tracking is an interesting but challenging task in computer vision field.
Robust Multi-resolution Pedestrian Detection in Traffic Scenes
The model contains resolution aware transformations to map pedestrians in different resolutions to a common space, where a shared detector is constructed to distinguish pedestrians from background.
Towards Pose Robust Face Recognition
In this paper, we propose a novel method for pose robust face recognition towards practical applications, which is fast, pose robust and can work well under unconstrained environments.
Fast Matching by 2 Lines of Code for Large Scale Face Recognition Systems
However, the use of this method is very generic and not limited in face recognition, which can be easily generalized to other biometrics as a post-processing module.
