Search Results for author: Xiang Wu

Found 33 papers, 6 papers with code

Hierarchical Face Aging through Disentangled Latent Characteristics

no code implementations ECCV 2020 Pei-Pei Li, Huaibo Huang, Yibo Hu, Xiang Wu, Ran He, Zhenan Sun

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.

Age Estimation

One Backward from Ten Forward, Subsampling for Large-Scale Deep Learning

no code implementations27 Apr 2021 Chaosheng Dong, Xiaojie Jin, Weihao Gao, Yijia Wang, Hongyi Zhang, Xiang Wu, Jianchao Yang, Xiaobing Liu

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

no code implementations4 Feb 2021 Ting-Yi Wu, Yunghsiang S. Han, Zhengrui Li, Bo Bai, Gong Zhang, Liang Chen, Xiang Wu

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

1 code implementation ICCV 2021 Chaoyou Fu, Yibo Hu, Xiang Wu, Hailin Shi, Tao Mei, Ran He

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.

Neural Architecture Search Person Re-Identification

Imbalance Robust Softmax for Deep Embeeding Learning

no code implementations23 Nov 2020 Hao Zhu, Yang Yuan, Guosheng Hu, Xiang Wu, Neil Robertson

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.

Face Recognition Person Re-Identification

DVG-Face: Dual Variational Generation for Heterogeneous Face Recognition

1 code implementation20 Sep 2020 Chaoyou Fu, Xiang Wu, Yibo Hu, Huaibo Huang, Ran He

As a consequence, massive new diverse paired heterogeneous images with the same identity can be generated from noises.

Contrastive Learning Face Recognition +1

Deep Momentum Uncertainty Hashing

no code implementations17 Sep 2020 Chaoyou Fu, Guoli Wang, Xiang Wu, Qian Zhang, Ran He

It embodies the uncertainty of the hashing network to the corresponding input image.

Combinatorial Optimization

TF-NAS: Rethinking Three Search Freedoms of Latency-Constrained Differentiable Neural Architecture Search

1 code implementation ECCV 2020 Yibo Hu, Xiang Wu, Ran He

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.

Neural Architecture Search

HAMBox: Delving into Online High-quality Anchors Mining for Detecting Outer Faces

no code implementations19 Dec 2019 Yang Liu, Xu Tang, Xiang Wu, Junyu Han, Jingtuo Liu, Errui Ding

In this paper, we propose an Online High-quality Anchor Mining Strategy (HAMBox), which explicitly helps outer faces compensate with high-quality anchors.

Face Detection Frame +1

Semantic Regularization: Improve Few-shot Image Classification by Reducing Meta Shift

no code implementations18 Dec 2019 Da Chen, Yong-Liang Yang, Zunlei Feng, Xiang Wu, Mingli Song, Wenbin Li, Yuan He, Hui Xue, Feng Mao

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.

Few-Shot Image Classification General Classification +1

Dual Variational Generation for Low Shot Heterogeneous Face Recognition

no code implementations NeurIPS 2019 Chaoyou Fu, Xiang Wu, Yibo Hu, Huaibo Huang, Ran He

Specifically, we first introduce a dual variational autoencoder to represent a joint distribution of paired heterogeneous images.

Face Recognition Heterogeneous Face Recognition

Breaking the Glass Ceiling for Embedding-Based Classifiers for Large Output Spaces

no code implementations NeurIPS 2019 Chuan Guo, Ali Mousavi, Xiang Wu, Daniel N. Holtmann-Rice, Satyen Kale, Sashank Reddi, Sanjiv Kumar

In extreme classification settings, embedding-based neural network models are currently not competitive with sparse linear and tree-based methods in terms of accuracy.

Data Augmentation General Classification

Hierarchical Video Frame Sequence Representation with Deep Convolutional Graph Network

no code implementations2 Jun 2019 Feng Mao, Xiang Wu, Hui Xue, Rong Zhang

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.

Frame General Classification +2

Low-Rank Principal Eigenmatrix Analysis

no code implementations28 Apr 2019 Krishna Balasubramanian, Elynn Y. Chen, Jianqing Fan, Xiang Wu

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

no code implementations30 Mar 2019 Pei-Pei Li, Xiang Wu, Yibo Hu, Ran He, Zhenan Sun

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.

Face Generation Face Recognition +2

UVA: A Universal Variational Framework for Continuous Age Analysis

no code implementations30 Mar 2019 Pei-Pei Li, Huaibo Huang, Yibo Hu, Xiang Wu, Ran He, Zhenan Sun

UVA is the first attempt to achieve facial age analysis tasks, including age translation, age generation and age estimation, in a universal framework.

Age Estimation Translation

High Fidelity Face Manipulation with Extreme Poses and Expressions

no code implementations28 Mar 2019 Chaoyou Fu, Yibo Hu, Xiang Wu, Guoli Wang, Qian Zhang, Ran He

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.

Face Generation Face Recognition

Dual Variational Generation for Low-Shot Heterogeneous Face Recognition

1 code implementation25 Mar 2019 Chaoyou Fu, Xiang Wu, Yibo Hu, Huaibo Huang, Ran He

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.

Face Recognition Heterogeneous Face Recognition

Local Orthogonal Decomposition for Maximum Inner Product Search

no code implementations25 Mar 2019 Xiang Wu, Ruiqi Guo, Sanjiv Kumar, David Simcha

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

no code implementations20 Mar 2019 Xiang Wu, Ruiqi Guo, David Simcha, Dave Dopson, Sanjiv Kumar

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.

Network Embedding

A Blended Deep Learning Approach for Predicting User Intended Actions

no code implementations11 Oct 2018 Fei Tan, Zhi Wei, Jun He, Xiang Wu, Bo Peng, Haoran Liu, Zhenyu Yan

In this work, we focus on pre- dicting attrition, which is one of typical user intended actions.

Disentangled Variational Representation for Heterogeneous Face Recognition

no code implementations6 Sep 2018 Xiang Wu, Huaibo Huang, Vishal M. Patel, Ran He, Zhenan Sun

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.

Face Recognition Heterogeneous Face Recognition

Pose-Guided Photorealistic Face Rotation

no code implementations CVPR 2018 Yibo Hu, Xiang Wu, Bing Yu, Ran He, Zhenan Sun

Face rotation provides an effective and cheap way for data augmentation and representation learning of face recognition.

Data Augmentation Face Recognition +1

Adversarial Discriminative Heterogeneous Face Recognition

no code implementations12 Sep 2017 Lingxiao Song, Man Zhang, Xiang Wu, Ran He

This framework integrates cross-spectral face hallucination and discriminative feature learning into an end-to-end adversarial network.

Face Hallucination Face Recognition +1

Anti-Makeup: Learning A Bi-Level Adversarial Network for Makeup-Invariant Face Verification

no code implementations12 Sep 2017 Yi Li, Lingxiao Song, Xiang Wu, Ran He, Tieniu Tan

This paper proposes a learning from generation approach for makeup-invariant face verification by introducing a bi-level adversarial network (BLAN).

Face Verification

Wasserstein CNN: Learning Invariant Features for NIR-VIS Face Recognition

no code implementations8 Aug 2017 Ran He, Xiang Wu, Zhenan Sun, Tieniu Tan

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.

Face Recognition Heterogeneous Face Recognition

Attention-Set based Metric Learning for Video Face Recognition

no code implementations12 Apr 2017 Yibo Hu, Xiang Wu, Ran He

In this paper, we propose a novel Attention-Set based Metric Learning (ASML) method to measure the statistical characteristics of image sets.

Face Recognition Metric Learning

Coupled Deep Learning for Heterogeneous Face Recognition

no code implementations8 Apr 2017 Xiang Wu, Lingxiao Song, Ran He, Tieniu Tan

CDL seeks a shared feature space in which the heterogeneous face matching problem can be approximately treated as a homogeneous face matching problem.

Face Recognition Heterogeneous Face Recognition

Learning Scene-specific Object Detectors Based on a Generative-Discriminative Model with Minimal Supervision

no code implementations12 Nov 2016 Dapeng Luo, Zhipeng Zeng, Nong Sang, Xiang Wu, Longsheng Wei, Quanzheng Mou, Jun Cheng, Chen Luo

In this paper, the proposed framework takes a remarkably different direction to resolve the multi-scene detection problem in a bottom-up fashion.

Object Detection online learning +1

A Light CNN for Deep Face Representation with Noisy Labels

7 code implementations9 Nov 2015 Xiang Wu, Ran He, Zhenan Sun, Tieniu Tan

This paper presents a Light CNN framework to learn a compact embedding on the large-scale face data with massive noisy labels.

Face Identification Face Recognition +1

Learning Robust Deep Face Representation

1 code implementation17 Jul 2015 Xiang Wu

With the development of convolution neural network, more and more researchers focus their attention on the advantage of CNN for face recognition task.

Face Recognition

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