1.1k citations · 2.3k across the 45 of their papers we have counts for
46 papers
Dual Teacher Knowledge Distillation with Domain Alignment for Face Anti-spoofing
Zhe Kong, Wentian Zhang, Tao Wang +4
Face recognition systems have raised concerns due to their vulnerability to different presentation attacks, and system security has become an increasingly critical concern. Althoug…
Towards Real-World Blind Face Restoration with Generative Diffusion Prior
Xiaoxu Chen, Jingfan Tan, Tao Wang +3
Blind face restoration is an important task in computer vision and has gained significant attention due to its wide-range applications. Previous works mainly exploit facial priors…
Deep Video Restoration for Under-Display Camera
Xuanxi Chen, Tao Wang, Ziqian Shao +6
Images or videos captured by the Under-Display Camera (UDC) suffer from severe degradation, such as saturation degeneration and color shift. While restoration for UDC has been a cr…
MB-TaylorFormer: Multi-branch Efficient Transformer Expanded by Taylor Formula for Image Dehazing
Yuwei Qiu, Kaihao Zhang, Chenxi Wang +3
In recent years, Transformer networks are beginning to replace pure convolutional neural networks (CNNs) in the field of computer vision due to their global receptive field and ada…
InterTracker: Discovering and Tracking General Objects Interacting with Hands in the Wild
Yanyan Shao, Qi Ye, Wenhan Luo +2
Understanding human interaction with objects is an important research topic for embodied Artificial Intelligence and identifying the objects that humans are interacting with is a p…
Blind Face Restoration for Under-Display Camera via Dictionary Guided Transformer
Jingfan Tan, Xiaoxu Chen, Tao Wang +3
By hiding the front-facing camera below the display panel, Under-Display Camera (UDC) provides users with a full-screen experience. However, due to the characteristics of the displ…
Benchmarking Ultra-High-Definition Image Reflection Removal
Zhenyuan Zhang, Zhenbo Song, Kaihao Zhang +2
Deep learning based methods have achieved significant success in the task of single image reflection removal (SIRR). However, the majority of these methods are focused on High-Defi…
LLDiffusion: Learning Degradation Representations in Diffusion Models for Low-Light Image Enhancement
Tao Wang, Kaihao Zhang, Ziqian Shao +5
Current deep learning methods for low-light image enhancement (LLIE) typically rely on pixel-wise mapping learned from paired data. However, these methods often overlook the import…
HTNet for micro-expression recognition
Zhifeng Wang, Kaihao Zhang, Wenhan Luo +1
Facial expression is related to facial muscle contractions and different muscle movements correspond to different emotional states. For micro-expression recognition, the muscle mov…
DREAM: Domain-free Reverse Engineering Attributes of Black-box Model
Rongqing Li, Jiaqi Yu, Changsheng Li +3
Deep learning models are usually black boxes when deployed on machine learning platforms. Prior works have shown that the attributes (, the number of convolutional layers) of…
PRIOR: Prototype Representation Joint Learning from Medical Images and Reports
Pujin Cheng, Li Lin, Junyan Lyu +3
Contrastive learning based vision-language joint pre-training has emerged as a successful representation learning strategy. In this paper, we present a prototype representation lea…
GridFormer: Residual Dense Transformer with Grid Structure for Image Restoration in Adverse Weather Conditions
Tao Wang, Kaihao Zhang, Ziqian Shao +6
Image restoration in adverse weather conditions is a difficult task in computer vision. In this paper, we propose a novel transformer-based framework called GridFormer which serves…
Learning Enhancement From Degradation: A Diffusion Model For Fundus Image Enhancement
Puijin Cheng, Li Lin, Yijin Huang +3
The quality of a fundus image can be compromised by numerous factors, many of which are challenging to be appropriately and mathematically modeled. In this paper, we introduce a no…
Ultra-High-Definition Low-Light Image Enhancement: A Benchmark and Transformer-Based Method
Tao Wang, Kaihao Zhang, Tianrun Shen +3
As the quality of optical sensors improves, there is a need for processing large-scale images. In particular, the ability of devices to capture ultra-high definition (UHD) images a…
Restoring Vision in Hazy Weather with Hierarchical Contrastive Learning
Tao Wang, Guangpin Tao, Wanglong Lu +4
Image restoration under hazy weather condition, which is called single image dehazing, has been of significant interest for various computer vision applications. In recent years, d…
ADTR: Anomaly Detection Transformer with Feature Reconstruction
Zhiyuan You, Kai Yang, Wenhan Luo +3
Anomaly detection with only prior knowledge from normal samples attracts more attention because of the lack of anomaly samples. Existing CNN-based pixel reconstruction approaches s…
Blind Face Restoration: Benchmark Datasets and a Baseline Model
Puyang Zhang, Kaihao Zhang, Wenhan Luo +2
Blind Face Restoration (BFR) aims to construct a high-quality (HQ) face image from its corresponding low-quality (LQ) input. Recently, many BFR methods have been proposed and they…
Multi-Prior Learning via Neural Architecture Search for Blind Face Restoration
Yanjiang Yu, Puyang Zhang, Kaihao Zhang +4
Blind Face Restoration (BFR) aims to recover high-quality face images from low-quality ones and usually resorts to facial priors for improving restoration performance. However, cur…
Aesthetic Text Logo Synthesis via Content-aware Layout Inferring
Yizhi Wang, Guo Pu, Wenhan Luo +4
Text logo design heavily relies on the creativity and expertise of professional designers, in which arranging element layouts is one of the most important procedures. However, few…
Deep Image Deblurring: A Survey
Kaihao Zhang, Wenqi Ren, Wenhan Luo +4
Image deblurring is a classic problem in low-level computer vision with the aim to recover a sharp image from a blurred input image. Advances in deep learning have led to significa…
Few-shot Object Counting with Similarity-Aware Feature Enhancement
Zhiyuan You, Kai Yang, Wenhan Luo +3
This work studies the problem of few-shot object counting, which counts the number of exemplar objects (i.e., described by one or several support images) occurring in the query ima…
MC-Blur: A Comprehensive Benchmark for Image Deblurring
Kaihao Zhang, Tao Wang, Wenhan Luo +6
Blur artifacts can seriously degrade the visual quality of images, and numerous deblurring methods have been proposed for specific scenarios. However, in most real-world images, bl…
EDFace-Celeb-1M: Benchmarking Face Hallucination with a Million-scale Dataset
Kaihao Zhang, Dongxu Li, Wenhan Luo +4
Recent deep face hallucination methods show stunning performance in super-resolving severely degraded facial images, even surpassing human ability. However, these algorithms are ma…
Taming Self-Supervised Learning for Presentation Attack Detection: De-Folding and De-Mixing
Zhe Kong, Wentian Zhang, Feng Liu +4
Biometric systems are vulnerable to Presentation Attacks (PA) performed using various Presentation Attack Instruments (PAIs). Even though there are numerous Presentation Attack Det…