Search Results for author: Hailin Shi

Found 34 papers, 15 papers with code

I2Edit: Towards Multi-turn Interactive Image Editing via Dialogue

no code implementations20 Mar 2023 Xing Cui, Zekun Li, Peipei Li, Yibo Hu, Hailin Shi, Zhaofeng He

The dataset is constructed upon the CelebA-HQ dataset with images annotated with a multi-turn dialogue that corresponds to the user editing requirements.

Facial Editing

Scale Attention for Learning Deep Face Representation: A Study Against Visual Scale Variation

no code implementations19 Sep 2022 Hailin Shi, Hang Du, Yibo Hu, Jun Wang, Dan Zeng, Ting Yao

Such multi-shot scheme brings inference burden, and the predefined scales inevitably have gap from real data.

Face Recognition

PetsGAN: Rethinking Priors for Single Image Generation

2 code implementations3 Mar 2022 ZiCheng Zhang, Yinglu Liu, Congying Han, Hailin Shi, Tiande Guo, BoWen Zhou

Moreover, we apply our method to other image manipulation tasks (e. g., style transfer, harmonization), and the results further prove the effectiveness and efficiency of our method.

Image Generation Image Manipulation +2

Dual Spoof Disentanglement Generation for Face Anti-spoofing with Depth Uncertainty Learning

1 code implementation1 Dec 2021 Hangtong Wu, Dan Zen, Yibo Hu, Hailin Shi, Tao Mei

Such noisy samples are hard to predict precise depth values, thus may obstruct the widely-used depth supervised optimization.

Disentanglement Face Anti-Spoofing +1

FasterPose: A Faster Simple Baseline for Human Pose Estimation

no code implementations7 Jul 2021 Hanbin Dai, Hailin Shi, Wu Liu, Linfang Wang, Yinglu Liu, Tao Mei

By the experimental analysis, we find that the HR representation leads to a sharp increase of computational cost, while the accuracy improvement remains marginal compared with the low-resolution (LR) representation.

Pose Estimation

Boosting Semi-Supervised Face Recognition with Noise Robustness

1 code implementation10 May 2021 Yuchi Liu, Hailin Shi, Hang Du, Rui Zhu, Jun Wang, Liang Zheng, Tao Mei

This paper presents an effective solution to semi-supervised face recognition that is robust to the label noise aroused by the auto-labelling.

Face Recognition

Multi-Agent Semi-Siamese Training for Long-tail and Shallow Face Learning

no code implementations10 May 2021 Hailin Shi, Dan Zeng, Yichun Tai, Hang Du, Yibo Hu, ZiCheng Zhang, Tao Mei

However, unlike the existing public face datasets, in many real-world scenarios of face recognition, the depth of training dataset is shallow, which means only two face images are available for each ID.

Face Recognition

Towards NIR-VIS Masked Face Recognition

no code implementations14 Apr 2021 Hang Du, Hailin Shi, Yinglu Liu, Dan Zeng, Tao Mei

In this paper, we aim to address the challenge of NIR-VIS masked face recognition from the perspectives of training data and training method.

3D Face Reconstruction Face Recognition +1

Dive into Ambiguity: Latent Distribution Mining and Pairwise Uncertainty Estimation for Facial Expression Recognition

1 code implementation CVPR 2021 Jiahui She, Yibo Hu, Hailin Shi, Jun Wang, Qiu Shen, Tao Mei

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 ambiguity.

Facial Expression Recognition (FER)

CM-NAS: Cross-Modality Neural Architecture Search for Visible-Infrared Person Re-Identification

1 code implementation ICCV 2021 Chaoyou Fu, Yibo Hu, Xiang Wu, Hailin Shi, Tao Mei, Ran He

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 environment.

Neural Architecture Search Person Re-Identification

FaceX-Zoo: A PyTorch Toolbox for Face Recognition

2 code implementations12 Jan 2021 Jun Wang, Yinglu Liu, Yibo Hu, Hailin Shi, Tao Mei

For example, the production of face representation network desires a modular training scheme to consider the proper choice from various candidates of state-of-the-art backbone and training supervision subject to the real-world face recognition demand; for performance analysis and comparison, the standard and automatic evaluation with a bunch of models on multiple benchmarks will be a desired tool as well; besides, a public groundwork is welcomed for deploying the face recognition in the shape of holistic pipeline.

Face Recognition

Edge-aware Graph Representation Learning and Reasoning for Face Parsing

1 code implementation ECCV 2020 Gusi Te, Yinglu Liu, Wei Hu, Hailin Shi, Tao Mei

Specifically, we encode a facial image onto a global graph representation where a collection of pixels ("regions") with similar features are projected to each vertex.

Face Parsing Graph Representation Learning

NPCFace: Negative-Positive Collaborative Training for Large-scale Face Recognition

no code implementations20 Jul 2020 Dan Zeng, Hailin Shi, Hang Du, Jun Wang, Zhen Lei, Tao Mei

However, the correlation between hard positive and hard negative is overlooked, and so is the relation between the margins in positive and negative logits.

Face Recognition

Semi-Siamese Training for Shallow Face Learning

2 code implementations ECCV 2020 Hang Du, Hailin Shi, Yuchi Liu, Jun Wang, Zhen Lei, Dan Zeng, Tao Mei

Extensive experiments on various benchmarks of face recognition show the proposed method significantly improves the training, not only in shallow face learning, but also for conventional deep face data.

Face Recognition

A New Dataset and Boundary-Attention Semantic Segmentation for Face Parsing

no code implementations Proceedings of the AAAI Conference on Artificial Intelligence 2020 Yinglu Liu, Hailin Shi, Hao Shen, Yue Si, Xiaobo Wang, Tao Mei

The dataset is publicly accessible to the community for boosting the advance of face parsing. 1 Second, a simple yet effective Boundary-Attention Semantic Segmentation (BASS) method is proposed for face parsing, which contains a three-branch network with elaborately developed loss functions to fully exploit the boundary information.

Face Parsing Image Generation +1

Mis-classified Vector Guided Softmax Loss for Face Recognition

no code implementations26 Nov 2019 Xiaobo Wang, Shifeng Zhang, Shuo Wang, Tianyu Fu, Hailin Shi, Tao Mei

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 discrimination.

Face Recognition

MetaAdvDet: Towards Robust Detection of Evolving Adversarial Attacks

1 code implementation6 Aug 2019 Chen Ma, Chenxu Zhao, Hailin Shi, Li Chen, Junhai Yong, Dan Zeng

To solve such few-shot problem with the evolving attack, we propose a meta-learning based robust detection method to detect new adversarial attacks with limited examples.

Adversarial Attack Detection Meta-Learning

A High-Efficiency Framework for Constructing Large-Scale Face Parsing Benchmark

no code implementations13 May 2019 Yinglu Liu, Hailin Shi, Yue Si, Hao Shen, Xiaobo Wang, Tao Mei

Each image is provided with accurate annotation of a 11-category pixel-level label map along with coordinates of 106-point landmarks.

Face Alignment Face Detection +3

Grand Challenge of 106-Point Facial Landmark Localization

no code implementations9 May 2019 Yinglu Liu, Hao Shen, Yue Si, Xiaobo Wang, Xiangyu Zhu, Hailin Shi, Zhibin Hong, Hanqi Guo, Ziyuan Guo, Yanqin Chen, Bi Li, Teng Xi, Jun Yu, Haonian Xie, Guochen Xie, Mengyan Li, Qing Lu, Zengfu Wang, Shenqi Lai, Zhenhua Chai, Xiaoming Wei

However, previous competitions on facial landmark localization (i. e., the 300-W, 300-VW and Menpo challenges) aim to predict 68-point landmarks, which are incompetent to depict the structure of facial components.

Face Alignment Face Recognition +2

Improved Selective Refinement Network for Face Detection

no code implementations20 Jan 2019 Shifeng Zhang, Rui Zhu, Xiaobo Wang, Hailin Shi, Tianyu Fu, Shuo Wang, Tao Mei, Stan Z. Li

With the availability of face detection benchmark WIDER FACE dataset, much of the progresses have been made by various algorithms in recent years.

Data Augmentation Face Detection +1

Support Vector Guided Softmax Loss for Face Recognition

3 code implementations29 Dec 2018 Xiaobo Wang, Shuo Wang, Shifeng Zhang, Tianyu Fu, Hailin Shi, Tao Mei

Face recognition has witnessed significant progresses due to the advances of deep convolutional neural networks (CNNs), the central challenge of which, is feature discrimination.

Face Recognition

A Dataset and Benchmark for Large-scale Multi-modal Face Anti-spoofing

2 code implementations CVPR 2019 Shifeng Zhang, Xiaobo Wang, Ajian Liu, Chenxu Zhao, Jun Wan, Sergio Escalera, Hailin Shi, Zezheng Wang, Stan Z. Li

To facilitate face anti-spoofing research, we introduce a large-scale multi-modal dataset, namely CASIA-SURF, which is the largest publicly available dataset for face anti-spoofing in terms of both subjects and visual modalities.

Face Anti-Spoofing Face Recognition

ScratchDet: Training Single-Shot Object Detectors from Scratch

1 code implementation CVPR 2019 Rui Zhu, Shifeng Zhang, Xiaobo Wang, Longyin Wen, Hailin Shi, Liefeng Bo, Tao Mei

Taking this advantage, we are able to explore various types of networks for object detection, without suffering from the poor convergence.

General Classification object-detection +1

Large-scale Bisample Learning on ID Versus Spot Face Recognition

no code implementations8 Jun 2018 Xiangyu Zhu, Hao liu, Zhen Lei, Hailin Shi, Fan Yang, Dong Yi, Guo-Jun Qi, Stan Z. Li

In this paper, we propose a deep learning based large-scale bisample learning (LBL) method for IvS face recognition.

Face Recognition General Classification

S3FD: Single Shot Scale-Invariant Face Detector

no code implementations ICCV 2017 Shifeng Zhang, Xiangyu Zhu, Zhen Lei, Hailin Shi, Xiaobo Wang, Stan Z. Li

This paper presents a real-time face detector, named Single Shot Scale-invariant Face Detector (S3FD), which performs superiorly on various scales of faces with a single deep neural network, especially for small faces.

Face Detection

FaceBoxes: A CPU Real-time Face Detector with High Accuracy

8 code implementations17 Aug 2017 Shifeng Zhang, Xiangyu Zhu, Zhen Lei, Hailin Shi, Xiaobo Wang, Stan Z. Li

The MSCL aims at enriching the receptive fields and discretizing anchors over different layers to handle faces of various scales.

Face Detection Vocal Bursts Intensity Prediction

S$^3$FD: Single Shot Scale-invariant Face Detector

3 code implementations17 Aug 2017 Shifeng Zhang, Xiangyu Zhu, Zhen Lei, Hailin Shi, Xiaobo Wang, Stan Z. Li

This paper presents a real-time face detector, named Single Shot Scale-invariant Face Detector (S$^3$FD), which performs superiorly on various scales of faces with a single deep neural network, especially for small faces.

Face Detection

Embedding Deep Metric for Person Re-identication A Study Against Large Variations

no code implementations1 Nov 2016 Hailin Shi, Yang Yang, Xiangyu Zhu, Shengcai Liao, Zhen Lei, Wei-Shi Zheng, Stan Z. Li

From this point of view, selecting suitable positive i. e. intra-class) training samples within a local range is critical for training the CNN embedding, especially when the data has large intra-class variations.

Person Re-Identification

Constrained Deep Metric Learning for Person Re-identification

no code implementations24 Nov 2015 Hailin Shi, Xiangyu Zhu, Shengcai Liao, Zhen Lei, Yang Yang, Stan Z. Li

In this paper, we propose a novel CNN-based method to learn a discriminative metric with good robustness to the over-fitting problem in person re-identification.

Metric Learning Person Re-Identification

Face Alignment Across Large Poses: A 3D Solution

no code implementations CVPR 2016 Xiangyu Zhu, Zhen Lei, Xiaoming Liu, Hailin Shi, Stan Z. Li

Face alignment, which fits a face model to an image and extracts the semantic meanings of facial pixels, has been an important topic in CV community.

3D Face Reconstruction Face Alignment +2

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