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20182022
most cited3D Face Reconstruction from A Single Image Assisted by 2D Face Images in the Wild

105 citations · 261 across the 15 of their papers we have counts for

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Showing 2019Show all

9 papers · 1 filter

cs.CV2019★ 1 cited

Defending from adversarial examples with a two-stream architecture

Hao Ge, Xiaoguang Tu, Mei Xie +1

In recent years, deep learning has shown impressive performance on many tasks. However, recent researches showed that deep learning systems are vulnerable to small, specially craft…

cs.CV2019★ 1 cited

STELA: A Real-Time Scene Text Detector with Learned Anchor

Linjie Deng, Yanxiang Gong, Xinchen Lu +3

To achieve high coverage of target boxes, a normal strategy of conventional one-stage anchor-based detectors is to utilize multiple priors at each spatial position, especially in s…

cs.CV2019★ 14 cited

Focus-Enhanced Scene Text Recognition with Deformable Convolutions

Linjie Deng, Yanxiang Gong, Xinchen Lu +3

Recently, scene text recognition methods based on deep learning have sprung up in computer vision area. The existing methods achieved great performances, but the recognition of irr…

cs.CV2019

Learning Robust 3D Face Reconstruction and Discriminative Identity Representation

Yao Luo, Xiaoguang Tu, Mei Xie

3D face reconstruction from a single 2D image is a very important topic in computer vision. However, the current reconstruction methods are usually non-sensitive to face identities…

cs.CV2019★ 105 cited

3D Face Reconstruction from A Single Image Assisted by 2D Face Images in the Wild

Xiaoguang Tu, Jian Zhao, Zihang Jiang +6

3D face reconstruction from a single 2D image is a challenging problem with broad applications. Recent methods typically aim to learn a CNN-based 3D face model that regresses coeff…

cs.CV2019★ 8 cited

Generating Text Sequence Images for Recognition

Yanxiang Gong, Linjie Deng, Zheng Ma +1

Recently, methods based on deep learning have dominated the field of text recognition. With a large number of training data, most of them can achieve the state-of-the-art performan…

cs.CV2019★ 27 cited

Enhance the Motion Cues for Face Anti-Spoofing using CNN-LSTM Architecture

Xiaoguang Tu, Hengsheng Zhang, Mei Xie +3

Spatio-temporal information is very important to capture the discriminative cues between genuine and fake faces from video sequences. To explore such a temporal feature, the fine-g…

cs.CV2019★ 22 cited

Learning Generalizable and Identity-Discriminative Representations for Face Anti-Spoofing

Xiaoguang Tu, Jian Zhao, Mei Xie +5

Face anti-spoofing (a.k.a presentation attack detection) has drawn growing attention due to the high-security demand in face authentication systems. Existing CNN-based approaches u…

cs.CV2019★ 28 cited

Deep Transfer Across Domains for Face Anti-spoofing

Xiaoguang Tu, Hengsheng Zhang, Mei Xie +3

A practical face recognition system demands not only high recognition performance, but also the capability of detecting spoofing attacks. While emerging approaches of face anti-spo…