Search Results for author: Shengcai Liao

Found 40 papers, 21 papers with code

Exclusivity-Consistency Regularized Knowledge Distillation for Face Recognition

no code implementations ECCV 2020 Xiaobo Wang, Tianyu Fu, Shengcai Liao, Shuo Wang, Zhen Lei, Tao Mei

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.

Face Recognition Knowledge Distillation

Unsupervised Domain Adaptation with Noise Resistible Mutual-Training for Person Re-identification

no code implementations ECCV 2020 Fang Zhao, Shengcai Liao, Guo-Sen Xie, Jian Zhao, Kaihao Zhang, Ling Shao

On the other hand, mutual instance selection further selects reliable and informative instances for training according to the peer-confidence and relationship disagreement of the networks.

Person Re-Identification Unsupervised Domain Adaptation

Cloning Outfits from Real-World Images to 3D Characters for Generalizable Person Re-Identification

1 code implementation6 Apr 2022 Yanan Wang, Xuezhi Liang, Shengcai Liao

To address this, in this work, an automatic approach is proposed to directly clone the whole outfits from real-world person images to virtual 3D characters, such that any virtual person thus created will appear very similar to its real-world counterpart.

Generalizable Person Re-identification

Pedestrian Detection: Domain Generalization, CNNs, Transformers and Beyond

2 code implementations10 Jan 2022 Irtiza Hasan, Shengcai Liao, Jinpeng Li, Saad Ullah Akram, Ling Shao

As for the data, we show that the autonomous driving benchmarks are monotonous in nature, that is, they are not diverse in scenarios and dense in pedestrians.

Autonomous Driving Domain Generalization +3

TAL: Two-stream Adaptive Learning for Generalizable Person Re-identification

no code implementations29 Nov 2021 Yichao Yan, Junjie Li, Shengcai Liao, Jie Qin, Bingbing Ni, Xiaokang Yang

In the meantime, we design an adaptive BN layer in the domain-invariant stream, to approximate the statistics of various unseen domains.

Domain Generalization Generalizable Person Re-identification

Efficient Person Search: An Anchor-Free Approach

1 code implementation1 Sep 2021 Yichao Yan, Jinpeng Li, Jie Qin, Shengcai Liao, Xiaokang Yang

Third, by investigating the advantages of both anchor-based and anchor-free models, we further augment AlignPS with an ROI-Align head, which significantly improves the robustness of re-id features while still keeping our model highly efficient.

Person Search

Learning Anchored Unsigned Distance Functions with Gradient Direction Alignment for Single-view Garment Reconstruction

1 code implementation ICCV 2021 Fang Zhao, Wenhao Wang, Shengcai Liao, Ling Shao

While single-view 3D reconstruction has made significant progress benefiting from deep shape representations in recent years, garment reconstruction is still not solved well due to open surfaces, diverse topologies and complex geometric details.

3D Reconstruction Single-View 3D Reconstruction

AFAN: Augmented Feature Alignment Network for Cross-Domain Object Detection

no code implementations10 Jun 2021 Hongsong Wang, Shengcai Liao, Ling Shao

Last but not least, we introduce a region feature alignment and an instance discriminator to learn domain-invariant features for object proposals.

Image Generation Object Detection +1

When Liebig's Barrel Meets Facial Landmark Detection: A Practical Model

no code implementations27 May 2021 Haibo Jin, Jinpeng Li, Shengcai Liao, Ling Shao

To this end, we first propose a baseline model equipped with one transformer decoder as detection head.

Facial Landmark Detection

Graph Sampling Based Deep Metric Learning for Generalizable Person Re-Identification

1 code implementation4 Apr 2021 Shengcai Liao, Ling Shao

Though online hard example mining has improved the learning efficiency to some extent, the mining in mini batches after random sampling is still limited.

Generalizable Person Re-identification Graph Sampling +3

Anchor-Free Person Search

1 code implementation CVPR 2021 Yichao Yan, Jinpeng Li, Jie Qin, Song Bai, Shengcai Liao, Li Liu, Fan Zhu, Ling Shao

Person search aims to simultaneously localize and identify a query person from realistic, uncropped images, which can be regarded as the unified task of pedestrian detection and person re-identification (re-id).

Pedestrian Detection Person Re-Identification +1

Human Parsing Based Texture Transfer from Single Image to 3D Human via Cross-View Consistency

1 code implementation NeurIPS 2020 Fang Zhao, Shengcai Liao, Kaihao Zhang, Ling Shao

This paper proposes a human parsing based texture transfer model via cross-view consistency learning to generate the texture of 3D human body from a single image.

Human Parsing Semantic Parsing +1

Surpassing Real-World Source Training Data: Random 3D Characters for Generalizable Person Re-Identification

1 code implementation23 Jun 2020 Yanan Wang, Shengcai Liao, Ling Shao

To address this, we propose to automatically synthesize a large-scale person re-identification dataset following a set-up similar to real surveillance but with virtual environments, and then use the synthesized person images to train a generalizable person re-identification model.

Domain Generalization Generalizable Person Re-identification +1

Attentive WaveBlock: Complementarity-enhanced Mutual Networks for Unsupervised Domain Adaptation in Person Re-identification and Beyond

1 code implementation11 Jun 2020 Wenhao Wang, Fang Zhao, Shengcai Liao, Ling Shao

This paper proposes a novel light-weight module, the Attentive WaveBlock (AWB), which can be integrated into the dual networks of mutual learning to enhance the complementarity and further depress noise in the pseudo-labels.

Image Classification Person Re-Identification +2

Generalizable Pedestrian Detection: The Elephant In The Room

1 code implementation CVPR 2021 Irtiza Hasan, Shengcai Liao, Jinpeng Li, Saad Ullah Akram, Ling Shao

Furthermore, we illustrate that diverse and dense datasets, collected by crawling the web, serve to be an efficient source of pre-training for pedestrian detection.

 Ranked #1 on Pedestrian Detection on CityPersons (using extra training data)

Autonomous Driving Pedestrian Detection

Pixel-in-Pixel Net: Towards Efficient Facial Landmark Detection in the Wild

1 code implementation8 Mar 2020 Haibo Jin, Shengcai Liao, Ling Shao

The proposed model is equipped with a novel detection head based on heatmap regression, which conducts score and offset predictions simultaneously on low-resolution feature maps.

Domain Generalization Facial Landmark Detection

Center and Scale Prediction: Anchor-free Approach for Pedestrian and Face Detection

2 code implementations CVPR 2019 Wei Liu, Irtiza Hasan, Shengcai Liao

Like edges, corners, blobs and other feature detectors, the proposed detector scans for feature points all over the image, for which the convolution is naturally suited.

Ranked #6 on Pedestrian Detection on Caltech (using extra training data)

Face Detection Object Detection +1

Pixel-aware Deep Function-mixture Network for Spectral Super-Resolution

no code implementations24 Mar 2019 Lei Zhang, Zhiqiang Lang, Peng Wang, Wei Wei, Shengcai Liao, Ling Shao, Yanning Zhang

To address this problem, we propose a pixel-aware deep function-mixture network for SSR, which is composed of a new class of modules, termed function-mixture (FM) blocks.

Super-Resolution

Vehicle Re-identification Using Quadruple Directional Deep Learning Features

no code implementations13 Nov 2018 Jianqing Zhu, Huanqiang Zeng, Jingchang Huang, Shengcai Liao, Zhen Lei, Canhui Cai, Lixin Zheng

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.

Vehicle Re-Identification

Learning Efficient Single-stage Pedestrian Detectors by Asymptotic Localization Fitting

1 code implementation ECCV 2018 Wei Liu, Shengcai Liao, Weidong Hu, Xuezhi Liang, Xiao Chen

However, current single-stage detectors (e. g. SSD) have not presented competitive accuracy on common pedestrian detection benchmarks.

Ranked #9 on Pedestrian Detection on Caltech (using extra training data)

Pedestrian Detection

Learning Efficient Image Representation for Person Re-Identification

no code implementations7 Jul 2017 Yang Yang, Shengcai Liao, Zhen Lei, Stan Z. Li

Then, a robust image representation based on color names is obtained by concatenating the statistical descriptors in each stripe.

Person Re-Identification

Deep Person Re-Identification with Improved Embedding and Efficient Training

1 code implementation9 May 2017 Haibo Jin, Xiaobo Wang, Shengcai Liao, Stan Z. Li

However, to achieve this, existing deep models prefer to adopt image pairs or triplets to form verification loss, which is inefficient and unstable since the number of training pairs or triplets grows rapidly as the number of training data grows.

Person Re-Identification

Deep Hybrid Similarity Learning for Person Re-identification

no code implementations16 Feb 2017 Jianqing Zhu, Huanqiang Zeng, Shengcai Liao, Zhen Lei, Canhui Cai, Lixin Zheng

In this paper, a deep hybrid similarity learning (DHSL) method for person Re-ID based on a convolution neural network (CNN) is proposed.

Metric Learning Person Re-Identification

Embedding Deep Metric for Person Re-identication A Study Against Large Variations

no code implementations1 Nov 2016 Hailin Shi, Yang Yang, Xiangyu Zhu, Shengcai Liao, Zhen Lei, Wei-Shi Zheng, Stan Z. Li

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.

Person Re-Identification

Partial Person Re-Identification

no code implementations ICCV 2015 Wei-Shi Zheng, Xiang Li, Tao Xiang, Shengcai Liao, Jian-Huang Lai, Shaogang Gong

We address a new partial person re-identification (re-id) problem, where only a partial observation of a person is available for matching across different non-overlapping camera views.

Person Re-Identification

Efficient PSD Constrained Asymmetric Metric Learning for Person Re-Identification

no code implementations ICCV 2015 Shengcai Liao, Stan Z. Li

We argue that the PSD constraint provides a useful regularization to smooth the solution of the metric, and hence the learned metric is more robust than without the PSD constraint.

Metric Learning Person Re-Identification

Constrained Deep Metric Learning for Person Re-identification

no code implementations24 Nov 2015 Hailin Shi, Xiangyu Zhu, Shengcai Liao, Zhen Lei, Yang Yang, Stan Z. Li

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.

Metric Learning Person Re-Identification

Learning Face Representation from Scratch

11 code implementations28 Nov 2014 Dong Yi, Zhen Lei, Shengcai Liao, Stan Z. Li

The current situation in the field of face recognition is that data is more important than algorithm.

Face Recognition

Cross-Modal Similarity Learning : A Low Rank Bilinear Formulation

no code implementations18 Nov 2014 Cuicui Kang, Shengcai Liao, Yonghao He, Jian Wang, Wenjia Niu, Shiming Xiang, Chunhong Pan

A new approach to the problem has been raised which intends to match features of different modalities directly.

Metric Learning

Open-set Person Re-identification

no code implementations5 Aug 2014 Shengcai Liao, Zhipeng Mo, Jianqing Zhu, Yang Hu, Stan Z. Li

Person re-identification is becoming a hot research for developing both machine learning algorithms and video surveillance applications.

Metric Learning Person Re-Identification

Person Re-identification by Local Maximal Occurrence Representation and Metric Learning

1 code implementation CVPR 2015 Shengcai Liao, Yang Hu, Xiangyu Zhu, Stan Z. Li

In this paper, we propose an effective feature representation called Local Maximal Occurrence (LOMO), and a subspace and metric learning method called Cross-view Quadratic Discriminant Analysis (XQDA).

Metric Learning Person Re-Identification

Shared Representation Learning for Heterogeneous Face Recognition

no code implementations5 Jun 2014 Dong Yi, Zhen Lei, Shengcai Liao, Stan Z. Li

For NIR-VIS problem, we produce new state-of-the-art performance on the CASIA HFB and NIR-VIS 2. 0 databases.

Face Recognition Heterogeneous Face Recognition +1

Robust Multi-resolution Pedestrian Detection in Traffic Scenes

no code implementations CVPR 2013 Junjie Yan, Xucong Zhang, Zhen Lei, Shengcai Liao, Stan Z. Li

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.

14 Pedestrian Detection

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