332 citations · 672 across the 15 of their papers we have counts for
16 papers
A Scale-Arbitrary Image Super-Resolution Network Using Frequency-domain Information
Jing Fang, Yinbo Yu, Zhongyuan Wang +2
Image super-resolution (SR) is a technique to recover lost high-frequency information in low-resolution (LR) images. Spatial-domain information has been widely exploited to impleme…
Real-time End-to-End Video Text Spotter with Contrastive Representation Learning
Wejia Wu, Zhuang Li, Jiahong Li +5
Video text spotting(VTS) is the task that requires simultaneously detecting, tracking and recognizing text in the video. Existing video text spotting methods typically develop soph…
Magic ELF: Image Deraining Meets Association Learning and Transformer
Kui Jiang, Zhongyuan Wang, Chen Chen +3
Convolutional neural network (CNN) and Transformer have achieved great success in multimedia applications. However, little effort has been made to effectively and efficiently harmo…
Deepfake Face Traceability with Disentangling Reversing Network
Jiaxin Ai, Zhongyuan Wang, Baojin Huang +1
Deepfake face not only violates the privacy of personal identity, but also confuses the public and causes huge social harm. The current deepfake detection only stays at the level o…
Domain Generalization via Shuffled Style Assembly for Face Anti-Spoofing
Zhuo Wang, Zezheng Wang, Zitong Yu +4
With diverse presentation attacks emerging continually, generalizable face anti-spoofing (FAS) has drawn growing attention. Most existing methods implement domain generalization (D…
Consistency Regularization for Deep Face Anti-Spoofing
Zezheng Wang, Zitong Yu, Xun Wang +7
Face anti-spoofing (FAS) plays a crucial role in securing face recognition systems. Empirically, given an image, a model with more consistent output on different views of this imag…
TANet: A new Paradigm for Global Face Super-resolution via Transformer-CNN Aggregation Network
Yuanzhi Wang, Tao Lu, Yanduo Zhang +4
Recently, face super-resolution (FSR) methods either feed whole face image into convolutional neural networks (CNNs) or utilize extra facial priors (e.g., facial parsing maps, faci…
Omniscient Video Super-Resolution
Peng Yi, Zhongyuan Wang, Kui Jiang +4
Most recent video super-resolution (SR) methods either adopt an iterative manner to deal with low-resolution (LR) frames from a temporally sliding window, or leverage the previousl…
Frequency-aware Discriminative Feature Learning Supervised by Single-Center Loss for Face Forgery Detection
Jiaming Li, Hongtao Xie, Jiahong Li +2
Face forgery detection is raising ever-increasing interest in computer vision since facial manipulation technologies cause serious worries. Though recent works have reached sound a…
When Face Recognition Meets Occlusion: A New Benchmark
Baojin Huang, Zhongyuan Wang, Guangcheng Wang +5
The existing face recognition datasets usually lack occlusion samples, which hinders the development of face recognition. Especially during the COVID-19 coronavirus epidemic, weari…
Degrade is Upgrade: Learning Degradation for Low-light Image Enhancement
Kui Jiang, Zhongyuan Wang, Zheng Wang +4
Low-light image enhancement aims to improve an image's visibility while keeping its visual naturalness. Different from existing methods tending to accomplish the relighting task di…
Metric Learning for Anti-Compression Facial Forgery Detection
Shenhao Cao, Qin Zou, Xiuqing Mao +1
Detecting facial forgery images and videos is an increasingly important topic in multimedia forensics. As forgery images and videos are usually compressed into different formats su…
Multi-Scale Progressive Fusion Network for Single Image Deraining
Kui Jiang, Zhongyuan Wang, Peng Yi +5
Rain streaks in the air appear in various blurring degrees and resolutions due to different distances from their positions to the camera. Similar rain patterns are visible in a rai…
Learning Inverse Rendering of Faces from Real-world Videos
Yuda Qiu, Zhangyang Xiong, Kai Han +3
In this paper we examine the problem of inverse rendering of real face images. Existing methods decompose a face image into three components (albedo, normal, and illumination) by s…
Masked Face Recognition Dataset and Application
Zhongyuan Wang, Guangcheng Wang, Baojin Huang +11
In order to effectively prevent the spread of COVID-19 virus, almost everyone wears a mask during coronavirus epidemic. This almost makes conventional facial recognition technology…
SuperPCA: A Superpixelwise PCA Approach for Unsupervised Feature Extraction of Hyperspectral Imagery
Junjun Jiang, Jiayi Ma, Chen Chen +3
As an unsupervised dimensionality reduction method, principal component analysis (PCA) has been widely considered as an efficient and effective preprocessing step for hyperspectral…