502 citations · 2.5k across the 78 of their papers we have counts for
21 papers · 1 filter
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…
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…
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…
Learning-based Real-time Detection of Intrinsic Reflectional Symmetry
Yi-Ling Qiao, Lin Gao, Shu-Zhi Liu +3
Reflectional symmetry is ubiquitous in nature. While extrinsic reflectional symmetry can be easily parametrized and detected, intrinsic symmetry is much harder due to the high solu…
LaplacianNet: Learning on 3D Meshes with Laplacian Encoding and Pooling
Yi-Ling Qiao, Lin Gao, Jie Yang +3
3D models are commonly used in computer vision and graphics. With the wider availability of mesh data, an efficient and intrinsic deep learning approach to processing 3D meshes is…
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…
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…
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…
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…
Segmentation Transformer: Object-Contextual Representations for Semantic Segmentation
Yuhui Yuan, Xiaokang Chen, Xilin Chen +1
In this paper, we address the semantic segmentation problem with a focus on the context aggregation strategy. Our motivation is that the label of a pixel is the category of the obj…
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…
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…
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…
Interlaced Sparse Self-Attention for Semantic Segmentation
Lang Huang, Yuhui Yuan, Jianyuan Guo +3
In this paper, we present a so-called interlaced sparse self-attention approach to improve the efficiency of the \emph{self-attention} mechanism for semantic segmentation. The main…
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…
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.…
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…
Retrieving Sequential Information for Non-Autoregressive Neural Machine Translation
Chenze Shao, Yang Feng, Jinchao Zhang +3
Non-Autoregressive Transformer (NAT) aims to accelerate the Transformer model through discarding the autoregressive mechanism and generating target words independently, which fails…
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…
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…
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…