Jiwen Lu

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PCANet: A Simple Deep Learning Baseline for Image Classification?

Tsung-Han Chan, Kui Jia, Shenghua Gao, Jiwen Lu, Zinan Zeng, Yi Ma
IEEE Transactions on Image Processing
2015

In this paper, we propose a very simple deep learning network for image classification that is based on very basic data processing components: 1) cascaded principal component analysis (PCA); 2)… (More)

Neighborhood repulsed metric learning for kinship verification

Jiwen Lu, Xiuzhuang Zhou, Yap-Peng Tan, Yuanyuan Shang, Jie Zhou
2012 IEEE Conference on Computer Vision and…
2012

Kinship verification from facial images is a challenging problem in computer vision, and there is a very few attempts on tackling this problem in the literature. In this paper, we propose a new… (More)

Discriminative Deep Metric Learning for Face Verification in the Wild

Junlin Hu, Jiwen Lu, Yap-Peng Tan
2014 IEEE Conference on Computer Vision and…
2014

This paper presents a new discriminative deep metric learning (DDML) method for face verification in the wild. Different from existing metric learning-based face verification methods which aim to… (More)

Deep hashing for compact binary codes learning

Venice Erin Liong, Jiwen Lu, Gang Wang, Pierre Moulin, Jie Zhou
2015 IEEE Conference on Computer Vision and…
2015

In this paper, we propose a new deep hashing (DH) approach to learn compact binary codes for large scale visual search. Unlike most existing binary codes learning methods which seek a single linear… (More)

A Siamese Long Short-Term Memory Architecture for Human Re-Identification

Rahul Rama Varior, Bing Shuai, Jiwen Lu, Dong Xu, Gang Wang
ECCV
2016

Matching pedestrians across multiple camera views known as human re-identification (re-identification) is a challenging problem in visual surveillance. In the existing works concentrating on feature… (More)

Discriminative Multimanifold Analysis for Face Recognition from a Single Training Sample per Person

Jiwen Lu, Yap-Peng Tan, Gang Wang
IEEE Transactions on Pattern Analysis and Machine…
2011

Conventional appearance-based face recognition methods usually assume that there are multiple samples per person (MSPP) available for discriminative feature extraction during the training phase. In… (More)

Learning Compact Binary Descriptors with Unsupervised Deep Neural Networks

Kevin Lin, Jiwen Lu, Chu-Song Chen, Jie Zhou
2016 IEEE Conference on Computer Vision and…
2016

In this paper, we propose a new unsupervised deep learning approach called DeepBit to learn compact binary descriptor for efficient visual object matching. Unlike most existing binary descriptors… (More)

Learning Compact Binary Face Descriptor for Face Recognition

Jiwen Lu, Venice Erin Liong, Xiuzhuang Zhou, Jie Zhou
IEEE Transactions on Pattern Analysis and Machine…
2015

Binary feature descriptors such as local binary patterns (LBP) and its variations have been widely used in many face recognition systems due to their excellent robustness and strong discriminative… (More)

Image Set Classification Using Holistic Multiple Order Statistics Features and Localized Multi-kernel Metric Learning

Jiwen Lu, Gang Wang, Pierre Moulin
2013 IEEE International Conference on Computer…
2013

This paper presents a new approach for image set classification, where each training and testing example contains a set of image instances of an object captured from varying viewpoints or under… (More)

Multi-manifold deep metric learning for image set classification

Jiwen Lu, Gang Wang, Weihong Deng, Pierre Moulin, Jie Zhou
2015 IEEE Conference on Computer Vision and…
2015

In this paper, we propose a multi-manifold deep metric learning (MMDML) method for image set classification, which aims to recognize an object of interest from a set of image instances captured from… (More)

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