Search Results for author: Xiaoguang Tu

Found 14 papers, 3 papers with code

Low-Light Image Enhancement by Learning Contrastive Representations in Spatial and Frequency Domains

no code implementations23 Mar 2023 Yi Huang, Xiaoguang Tu, Gui Fu, Tingting Liu, Bokai Liu, Ming Yang, Ziliang Feng

Images taken under low-light conditions tend to suffer from poor visibility, which can decrease image quality and even reduce the performance of the downstream tasks.

Contrastive Learning Low-Light Image Enhancement

Image-to-Video Generation via 3D Facial Dynamics

no code implementations31 May 2021 Xiaoguang Tu, Yingtian Zou, Jian Zhao, Wenjie Ai, Jian Dong, Yuan YAO, Zhikang Wang, Guodong Guo, Zhifeng Li, Wei Liu, Jiashi Feng

Video generation from a single face image is an interesting problem and usually tackled by utilizing Generative Adversarial Networks (GANs) to integrate information from the input face image and a sequence of sparse facial landmarks.

Image to Video Generation Video Prediction

Joint Face Image Restoration and Frontalization for Recognition

no code implementations12 May 2021 Xiaoguang Tu, Jian Zhao, Qiankun Liu, Wenjie Ai, Guodong Guo, Zhifeng Li, Wei Liu, Jiashi Feng

First, MDFR is a well-designed encoder-decoder architecture which extracts feature representation from an input face image with arbitrary low-quality factors and restores it to a high-quality counterpart.

Face Recognition Image Restoration

Single Image Super-Resolution via Residual Neuron Attention Networks

no code implementations21 May 2020 Wenjie Ai, Xiaoguang Tu, Shilei Cheng, Mei Xie

Experiments results demonstrate that our RNAN achieves the comparable results with state-of-the-art methods in terms of both quantitative metrics and visual quality, however, with simplified network architecture.

Image Super-Resolution

What's the relationship between CNNs and communication systems?

no code implementations3 Mar 2020 Hao Ge, Xiaoguang Tu, Yanxiang Gong, Mei Xie, Zheng Ma

The interpretability of Convolutional Neural Networks (CNNs) is an important topic in the field of computer vision.

Defending from adversarial examples with a two-stream architecture

no code implementations30 Dec 2019 Hao Ge, Xiaoguang Tu, Mei Xie, Zheng Ma

We demonstrate that our two-stream architecture is robust to adversarial examples built by currently known attacking algorithms.

Vocal Bursts Valence Prediction

Cross-Resolution Face Recognition via Prior-Aided Face Hallucination and Residual Knowledge Distillation

no code implementations26 May 2019 Hanyang Kong, Jian Zhao, Xiaoguang Tu, Junliang Xing, ShengMei Shen, Jiashi Feng

Recent deep learning based face recognition methods have achieved great performance, but it still remains challenging to recognize very low-resolution query face like 28x28 pixels when CCTV camera is far from the captured subject.

Face Hallucination Face Recognition +4

Multi-Prototype Networks for Unconstrained Set-based Face Recognition

no code implementations13 Feb 2019 Jian Zhao, Jianshu Li, Xiaoguang Tu, Fang Zhao, Yuan Xin, Junliang Xing, Hengzhu Liu, Shuicheng Yan, Jiashi Feng

In this paper, we study the challenging unconstrained set-based face recognition problem where each subject face is instantiated by a set of media (images and videos) instead of a single image.

Face Recognition

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

1 code implementation17 Jan 2019 Xiaoguang Tu, Jian Zhao, Mei Xie, Guodong Du, Hengsheng Zhang, Jianshu Li, Zheng Ma, Jiashi Feng

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

Domain Adaptation Face Anti-Spoofing +1

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

no code implementations17 Jan 2019 Xiaoguang Tu, Hengsheng Zhang, Mei Xie, Yao Luo, Yuefei Zhang, Zheng Ma

Spatio-temporal information is very important to capture the discriminative cues between genuine and fake faces from video sequences.

Face Anti-Spoofing Motion Magnification

Deep Transfer Across Domains for Face Anti-spoofing

no code implementations17 Jan 2019 Xiaoguang Tu, Hengsheng Zhang, Mei Xie, Yao Luo, Yuefei Zhang, Zheng Ma

We propose a CNN framework using sparsely labeled data from the target domain to learn features that are invariant across domains for face anti-spoofing.

Face Anti-Spoofing Face Recognition

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