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Found 37 papers, 6 papers with code
Hierarchical Face Aging through Disentangled Latent Characteristics
To explore the age effects on facial images, we propose a Disentangled Adversarial Autoencoder (DAAE) to disentangle the facial images into three independent factors: age, identity and extraneous information.
ScaDyG:A New Paradigm for Large-scale Dynamic Graph Learning
Dynamic graphs (DGs), which capture time-evolving relationships between graph entities, have widespread real-world applications.
SP-SLAM: Neural Real-Time Dense SLAM With Scene Priors
In this paper, we introduce SP-SLAM, a novel neural RGB-D SLAM system that performs tracking and mapping in real-time.
Simultaneous Localization and Mapping
Surface Reconstruction
A Two-phase On-line Joint Scheduling for Welfare Maximization of Charging Station
First, a joint scheduling model of pricing and charging control is developed to maximize the expected social welfare of the charging station considering the Quality of Service and the price fluctuation sensitivity of EV drivers.
Developmental Network Two, Its Optimality, and Emergent Turing Machines
By dynamic, we mean the automatic selection of features while disregarding distractors is not static, but instead based on dynamic statistics (e. g. because of the instability of shadows in the context of landmark).
One Backward from Ten Forward, Subsampling for Large-Scale Deep Learning
Deep learning models in large-scale machine learning systems are often continuously trained with enormous data from production environments.
Lower Bound on the Optimal Access Bandwidth of ($K+2,K,2$)-MDS Array Code with Degraded Read Friendly
Accessing the data in the failed disk (degraded read) with low latency is crucial for an erasure-coded storage system.
Information Theory Information Theory
CM-NAS: Cross-Modality Neural Architecture Search for Visible-Infrared Person Re-Identification
Visible-Infrared person re-identification (VI-ReID) aims to match cross-modality pedestrian images, breaking through the limitation of single-modality person ReID in dark environment.
Imbalance Robust Softmax for Deep Embeeding Learning
IR-Softmax can generalise to any softmax and its variants (which are discriminative for open-set problem) by directly setting the weights as their class centers, naturally solving the data imbalance problem.
DVG-Face: Dual Variational Generation for Heterogeneous Face Recognition
As a consequence, massive new diverse paired heterogeneous images with the same identity can be generated from noises.
Deep Momentum Uncertainty Hashing
It embodies the uncertainty of the hashing network to the corresponding input image.
TF-NAS: Rethinking Three Search Freedoms of Latency-Constrained Differentiable Neural Architecture Search
In this paper, we rethink three freedoms of differentiable NAS, i. e. operation-level, depth-level and width-level, and propose a novel method, named Three-Freedom NAS (TF-NAS), to achieve both good classification accuracy and precise latency constraint.
HAMBox: Delving into Online High-quality Anchors Mining for Detecting Outer Faces
In this paper, we propose an Online High-quality Anchor Mining Strategy (HAMBox), which explicitly helps outer faces compensate with high-quality anchors.
Semantic Regularization: Improve Few-shot Image Classification by Reducing Meta Shift
This strategy leads to severe meta shift issues across multiple tasks, meaning the learned prototypes or class descriptors are not stable as each task only involves their own support set.
Breaking the Glass Ceiling for Embedding-Based Classifiers for Large Output Spaces
In extreme classification settings, embedding-based neural network models are currently not competitive with sparse linear and tree-based methods in terms of accuracy.
Dual Variational Generation for Low Shot Heterogeneous Face Recognition
Specifically, we first introduce a dual variational autoencoder to represent a joint distribution of paired heterogeneous images.
Hierarchical Video Frame Sequence Representation with Deep Convolutional Graph Network
However, the video length is usually long, and there are hierarchical relationships between frames across events in the video, the performance of RNN based models are decreased.
Ranked #1 on
Video Classification
on YouTube-8M
Low-Rank Principal Eigenmatrix Analysis
Sparse PCA is a widely used technique for high-dimensional data analysis.
M2FPA: A Multi-Yaw Multi-Pitch High-Quality Database and Benchmark for Facial Pose Analysis
In this paper, a new large-scale Multi-yaw Multi-pitch high-quality database is proposed for Facial Pose Analysis (M2FPA), including face frontalization, face rotation, facial pose estimation and pose-invariant face recognition.
UVA: A Universal Variational Framework for Continuous Age Analysis
UVA is the first attempt to achieve facial age analysis tasks, including age translation, age generation and age estimation, in a universal framework.
High Fidelity Face Manipulation with Extreme Poses and Expressions
Furthermore, due to the lack of high-resolution face manipulation databases to verify the effectiveness of our method, we collect a new high-quality Multi-View Face (MVF-HQ) database.
Dual Variational Generation for Low-Shot Heterogeneous Face Recognition
Then, in order to ensure the identity consistency of the generated paired heterogeneous images, we impose a distribution alignment in the latent space and a pairwise identity preserving in the image space.
Ranked #1 on
Face Verification
on CASIA NIR-VIS 2.0
Local Orthogonal Decomposition for Maximum Inner Product Search
More specifically, we decompose a residual vector locally into two orthogonal components and perform uniform quantization and multiscale quantization to each component respectively.
Efficient Inner Product Approximation in Hybrid Spaces
In this paper, we propose a technique that approximates the inner product computation in hybrid vectors, leading to substantial speedup in search while maintaining high accuracy.
A Blended Deep Learning Approach for Predicting User Intended Actions
In this work, we focus on pre- dicting attrition, which is one of typical user intended actions.
Neurons Merging Layer: Towards Progressive Redundancy Reduction for Deep Supervised Hashing
It generates hashing bits by the output neurons of a deep hashing network.
Disentangled Variational Representation for Heterogeneous Face Recognition
Visible (VIS) to near infrared (NIR) face matching is a challenging problem due to the significant domain discrepancy between the domains and a lack of sufficient data for training cross-modal matching algorithms.
Ranked #2 on
Face Verification
on CASIA NIR-VIS 2.0
Pose-Guided Photorealistic Face Rotation
Face rotation provides an effective and cheap way for data augmentation and representation learning of face recognition.
Multiscale Quantization for Fast Similarity Search
We propose a multiscale quantization approach for fast similarity search on large, high-dimensional datasets.
Adversarial Discriminative Heterogeneous Face Recognition
This framework integrates cross-spectral face hallucination and discriminative feature learning into an end-to-end adversarial network.
Anti-Makeup: Learning A Bi-Level Adversarial Network for Makeup-Invariant Face Verification
This paper proposes a learning from generation approach for makeup-invariant face verification by introducing a bi-level adversarial network (BLAN).
Wasserstein CNN: Learning Invariant Features for NIR-VIS Face Recognition
To avoid the over-fitting problem on small-scale heterogeneous face data, a correlation prior is introduced on the fully-connected layers of WCNN network to reduce parameter space.
Ranked #3 on
Face Verification
on BUAA-VisNir
Attention-Set based Metric Learning for Video Face Recognition
In this paper, we propose a novel Attention-Set based Metric Learning (ASML) method to measure the statistical characteristics of image sets.
Coupled Deep Learning for Heterogeneous Face Recognition
CDL seeks a shared feature space in which the heterogeneous face matching problem can be approximately treated as a homogeneous face matching problem.
Learning Scene-specific Object Detectors Based on a Generative-Discriminative Model with Minimal Supervision
In this paper, the proposed framework takes a remarkably different direction to resolve the multi-scene detection problem in a bottom-up fashion.
A Light CNN for Deep Face Representation with Noisy Labels
This paper presents a Light CNN framework to learn a compact embedding on the large-scale face data with massive noisy labels.
Ranked #2 on
Age-Invariant Face Recognition
on CAFR
Learning Robust Deep Face Representation
With the development of convolution neural network, more and more researchers focus their attention on the advantage of CNN for face recognition task.
