406 citations · 1.3k across the 32 of their papers we have counts for
32 papers
CHATEDIT: Towards Multi-turn Interactive Facial Image Editing via Dialogue
Xing Cui, Zekun Li, Peipei Li +3
This paper explores interactive facial image editing via dialogue and introduces the ChatEdit benchmark dataset for evaluating image editing and conversation abilities in this cont…
Scale Attention for Learning Deep Face Representation: A Study Against Visual Scale Variation
Hailin Shi, Hang Du, Yibo Hu +3
Human face images usually appear with wide range of visual scales. The existing face representations pursue the bandwidth of handling scale variation via multi-scale scheme that as…
PetsGAN: Rethinking Priors for Single Image Generation
Zicheng Zhang, Yinglu Liu, Congying Han +3
Single image generation (SIG), described as generating diverse samples that have similar visual content with the given single image, is first introduced by SinGAN which builds a py…
Dual Spoof Disentanglement Generation for Face Anti-spoofing with Depth Uncertainty Learning
Hangtong Wu, Dan Zen, Yibo Hu +2
Face anti-spoofing (FAS) plays a vital role in preventing face recognition systems from presentation attacks. Existing face anti-spoofing datasets lack diversity due to the insuffi…
FasterPose: A Faster Simple Baseline for Human Pose Estimation
Hanbin Dai, Hailin Shi, Wu Liu +3
The performance of human pose estimation depends on the spatial accuracy of keypoint localization. Most existing methods pursue the spatial accuracy through learning the high-resol…
Boosting Semi-Supervised Face Recognition with Noise Robustness
Yuchi Liu, Hailin Shi, Hang Du +4
Although deep face recognition benefits significantly from large-scale training data, a current bottleneck is the labelling cost. A feasible solution to this problem is semi-superv…
Multi-Agent Semi-Siamese Training for Long-tail and Shallow Face Learning
Hailin Shi, Dan Zeng, Yichun Tai +4
With the recent development of deep convolutional neural networks and large-scale datasets, deep face recognition has made remarkable progress and been widely used in various appli…
Towards NIR-VIS Masked Face Recognition
Hang Du, Hailin Shi, Yinglu Liu +2
Near-infrared to visible (NIR-VIS) face recognition is the most common case in heterogeneous face recognition, which aims to match a pair of face images captured from two different…
Dive into Ambiguity: Latent Distribution Mining and Pairwise Uncertainty Estimation for Facial Expression Recognition
Jiahui She, Yibo Hu, Hailin Shi +3
Due to the subjective annotation and the inherent interclass similarity of facial expressions, one of key challenges in Facial Expression Recognition (FER) is the annotation ambigu…
CM-NAS: Cross-Modality Neural Architecture Search for Visible-Infrared Person Re-Identification
Chaoyou Fu, Yibo Hu, Xiang Wu +3
Visible-Infrared person re-identification (VI-ReID) aims to match cross-modality pedestrian images, breaking through the limitation of single-modality person ReID in dark environme…
AGRNet: Adaptive Graph Representation Learning and Reasoning for Face Parsing
Gusi Te, Wei Hu, Yinglu Liu +2
Face parsing infers a pixel-wise label to each facial component, which has drawn much attention recently. Previous methods have shown their success in face parsing, which however o…
FaceX-Zoo: A PyTorch Toolbox for Face Recognition
Jun Wang, Yinglu Liu, Yibo Hu +2
Deep learning based face recognition has achieved significant progress in recent years. Yet, the practical model production and further research of deep face recognition are in gre…
The Elements of End-to-end Deep Face Recognition: A Survey of Recent Advances
Hang Du, Hailin Shi, Dan Zeng +2
Face recognition is one of the most popular and long-standing topics in computer vision. With the recent development of deep learning techniques and large-scale datasets, deep face…
Edge-aware Graph Representation Learning and Reasoning for Face Parsing
Gusi Te, Yinglu Liu, Wei Hu +2
Face parsing infers a pixel-wise label to each facial component, which has drawn much attention recently. Previous methods have shown their efficiency in face parsing, which howeve…
Semi-Siamese Training for Shallow Face Learning
Hang Du, Hailin Shi, Yuchi Liu +4
Most existing public face datasets, such as MS-Celeb-1M and VGGFace2, provide abundant information in both breadth (large number of IDs) and depth (sufficient number of samples) fo…
NPCFace: Negative-Positive Collaborative Training for Large-scale Face Recognition
Dan Zeng, Hailin Shi, Hang Du +3
The training scheme of deep face recognition has greatly evolved in the past years, yet it encounters new challenges in the large-scale data situation where massive and diverse har…
Mis-classified Vector Guided Softmax Loss for Face Recognition
Xiaobo Wang, Shifeng Zhang, Shuo Wang +3
Face recognition has witnessed significant progress due to the advances of deep convolutional neural networks (CNNs), the central task of which is how to improve the feature discri…
MetaAdvDet: Towards Robust Detection of Evolving Adversarial Attacks
Chen Ma, Chenxu Zhao, Hailin Shi +3
Deep neural networks (DNNs) are vulnerable to adversarial attack which is maliciously implemented by adding human-imperceptible perturbation to images and thus leads to incorrect p…
A High-Efficiency Framework for Constructing Large-Scale Face Parsing Benchmark
Yinglu Liu, Hailin Shi, Yue Si +3
Face parsing, which is to assign a semantic label to each pixel in face images, has recently attracted increasing interest due to its huge application potentials. Although many fac…
Grand Challenge of 106-Point Facial Landmark Localization
Yinglu Liu, Hao Shen, Yue Si +18
Facial landmark localization is a very crucial step in numerous face related applications, such as face recognition, facial pose estimation, face image synthesis, etc. However, pre…
Improved Selective Refinement Network for Face Detection
Shifeng Zhang, Rui Zhu, Xiaobo Wang +5
As a long-standing problem in computer vision, face detection has attracted much attention in recent decades for its practical applications. With the availability of face detection…
Support Vector Guided Softmax Loss for Face Recognition
Xiaobo Wang, Shuo Wang, Shifeng Zhang +3
Face recognition has witnessed significant progresses due to the advances of deep convolutional neural networks (CNNs), the central challenge of which, is feature discrimination. T…
A Dataset and Benchmark for Large-scale Multi-modal Face Anti-spoofing
Shifeng Zhang, Xiaobo Wang, Ajian Liu +6
Face anti-spoofing is essential to prevent face recognition systems from a security breach. Much of the progresses have been made by the availability of face anti-spoofing benchmar…
ScratchDet: Training Single-Shot Object Detectors from Scratch
Rui Zhu, Shifeng Zhang, Xiaobo Wang +4
Current state-of-the-art object objectors are fine-tuned from the off-the-shelf networks pretrained on large-scale classification dataset ImageNet, which incurs some additional pro…