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20142024
most citedRhythmNet: End-to-end Heart Rate Estimation from Face via Spatial-temporal Representation

421 citations · 1.7k across the 83 of their papers we have counts for

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Showing 2019Show all

17 papers · 1 filter

cs.CV2019★ 20 cited

Deep Heterogeneous Hashing for Face Video Retrieval

Shishi Qiao, Ruiping Wang, Shiguang Shan +1

Retrieving videos of a particular person with face image as a query via hashing technique has many important applications. While face images are typically represented as vectors in…

cs.CV2019★ 3 cited

FCSR-GAN: Joint Face Completion and Super-resolution via Multi-task Learning

Jiancheng Cai, Hu Han, Shiguang Shan +1

Combined variations containing low-resolution and occlusion often present in face images in the wild, e.g., under the scenario of video surveillance. While most of the existing fac…

cs.CV2019★ 421 cited

RhythmNet: End-to-end Heart Rate Estimation from Face via Spatial-temporal Representation

Xuesong Niu, Shiguang Shan, Hu Han +1

Heart rate (HR) is an important physiological signal that reflects the physical and emotional status of a person. Traditional HR measurements usually rely on contact monitors, whic…

cs.CV2019★ 142 cited

Cross Attention Network for Few-shot Classification

Ruibing Hou, Hong Chang, Bingpeng Ma +2

Few-shot classification aims to recognize unlabeled samples from unseen classes given only few labeled samples. The unseen classes and low-data problem make few-shot classification…

cs.CV2019★ 11 cited

Cross-modal Scene Graph Matching for Relationship-aware Image-Text Retrieval

Sijin Wang, Ruiping Wang, Ziwei Yao +2

Image-text retrieval of natural scenes has been a popular research topic. Since image and text are heterogeneous cross-modal data, one of the key challenges is how to learn compreh…

cs.CV2019★ 31 cited

Multi-label Co-regularization for Semi-supervised Facial Action Unit Recognition

Xuesong Niu, Hu Han, Shiguang Shan +1

Facial action units (AUs) recognition is essential for emotion analysis and has been widely applied in mental state analysis. Existing work on AU recognition usually requires big f…

cs.CV2019★ 22 cited

Self-supervised Scale Equivariant Network for Weakly Supervised Semantic Segmentation

Yude Wang, Jie Zhang, Meina Kan +2

Weakly supervised semantic segmentation has attracted much research interest in recent years considering its advantage of low labeling cost. Most of the advanced algorithms follow…

cs.CV2019★ 23 cited

Transferable Contrastive Network for Generalized Zero-Shot Learning

Huajie Jiang, Ruiping Wang, Shiguang Shan +1

Zero-shot learning (ZSL) is a challenging problem that aims to recognize the target categories without seen data, where semantic information is leveraged to transfer knowledge from…

cs.CV2019★ 6 cited

Temporal Knowledge Propagation for Image-to-Video Person Re-identification

Xinqian Gu, Bingpeng Ma, Hong Chang +2

In many scenarios of Person Re-identification (Re-ID), the gallery set consists of lots of surveillance videos and the query is just an image, thus Re-ID has to be conducted betwee…

cs.CV2019★ 3 cited

CRIC: A VQA Dataset for Compositional Reasoning on Vision and Commonsense

Difei Gao, Ruiping Wang, Shiguang Shan +1

Alternatively inferring on the visual facts and commonsense is fundamental for an advanced VQA system. This ability requires models to go beyond the literal understanding of common…

cs.CV2019★ 39 cited

Interaction-and-Aggregation Network for Person Re-identification

Ruibing Hou, Bingpeng Ma, Hong Chang +3

Person re-identification (reID) benefits greatly from deep convolutional neural networks (CNNs) which learn robust feature embeddings. However, CNNs are inherently limited in model…

cs.CV2019★ 17 cited

VRSTC: Occlusion-Free Video Person Re-Identification

Ruibing Hou, Bingpeng Ma, Hong Chang +3

Video person re-identification (re-ID) plays an important role in surveillance video analysis. However, the performance of video re-ID degenerates severely under partial occlusion.…

cs.CV2019★ 50 cited

Cascade RetinaNet: Maintaining Consistency for Single-Stage Object Detection

Hongkai Zhang, Hong Chang, Bingpeng Ma +2

Recent researches attempt to improve the detection performance by adopting the idea of cascade for single-stage detectors. In this paper, we analyze and discover that inconsistency…

cs.CV2019★ 19 cited

Pose-adaptive Hierarchical Attention Network for Facial Expression Recognition

Yuanyuan Liu, Jiyao Peng, Jiabei Zeng +1

Multi-view facial expression recognition (FER) is a challenging task because the appearance of an expression varies in poses. To alleviate the influences of poses, recent methods e…

cs.CV2019★ 18 cited

Weakly Supervised Object Detection with Segmentation Collaboration

Xiaoyan Li, Meina Kan, Shiguang Shan +1

Weakly supervised object detection aims at learning precise object detectors, given image category labels. In recent prevailing works, this problem is generally formulated as a mul…

cs.CV2019★ 4 cited

Fully Learnable Group Convolution for Acceleration of Deep Neural Networks

Xijun Wang, Meina Kan, Shiguang Shan +1

Benefitted from its great success on many tasks, deep learning is increasingly used on low-computational-cost devices, e.g. smartphone, embedded devices, etc. To reduce the high co…

cs.CV2019★ 28 cited

WIDER Face and Pedestrian Challenge 2018: Methods and Results

Chen Change Loy, Dahua Lin, Wanli Ouyang +49

This paper presents a review of the 2018 WIDER Challenge on Face and Pedestrian. The challenge focuses on the problem of precise localization of human faces and bodies, and accurat…