1.5k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Nankai UniversityCN185 papers
- Chinese Academy of SciencesCN114 papers
- National University of SingaporeSG63 papers
- Tsinghua UniversityCN53 papers
- University of Chinese Academy of SciencesCN50 papers
- Peking UniversityCN48 papers
- Nanyang Technological UniversitySG43 papers
- Centre National de la Recherche ScientifiqueFR39 papers
- University of Science and Technology of ChinaCN37 papers
- Peng Huanwu Center for Fundamental TheoryCN31 papers
- Beijing Normal UniversityCN29 papers
- Lanzhou UniversityCN29 papers
20 papers · 2 filters
Global and Local Sensitivity Guided Key Salient Object Re-augmentation for Video Saliency Detection
Ziqi Zhou, Zheng Wang, Huchuan Lu +2
The existing still-static deep learning based saliency researches do not consider the weighting and highlighting of extracted features from different layers, all features contribut…
HSCS: Hierarchical Sparsity Based Co-saliency Detection for RGBD Images
Runmin Cong, Jianjun Lei, Huazhu Fu +3
Co-saliency detection aims to discover common and salient objects in an image group containing more than two relevant images. Moreover, depth information has been demonstrated to b…
RA-UNet: A hybrid deep attention-aware network to extract liver and tumor in CT scans
Qiangguo Jin, Zhaopeng Meng, Changming Sun +2
Automatic extraction of liver and tumor from CT volumes is a challenging task due to their heterogeneous and diffusive shapes. Recently, 2D and 3D deep convolutional neural network…
DUNet: A deformable network for retinal vessel segmentation
Qiangguo Jin, Zhaopeng Meng, Tuan D. Pham +3
Automatic segmentation of retinal vessels in fundus images plays an important role in the diagnosis of some diseases such as diabetes and hypertension. In this paper, we propose De…
Does Haze Removal Help CNN-based Image Classification?
Yanting Pei, Yaping Huang, Qi Zou +2
Hazy images are common in real scenarios and many dehazing methods have been developed to automatically remove the haze from images. Typically, the goal of image dehazing is to pro…
Triply Supervised Decoder Networks for Joint Detection and Segmentation
Jiale Cao, Yanwei Pang, Xuelong Li
Joint object detection and semantic segmentation can be applied to many fields, such as self-driving cars and unmanned surface vessels. An initial and important progress towards th…
SG-FCN: A Motion and Memory-Based Deep Learning Model for Video Saliency Detection
Meijun Sun, Ziqi Zhou, QinGhua Hu +2
Data-driven saliency detection has attracted strong interest as a result of applying convolutional neural networks to the detection of eye fixations. Although a number of imagebase…
Person Re-Identification by Semantic Region Representation and Topology Constraint
Jianjun Lei, Lijie Niu, Huazhu Fu +3
Person re-identification is a popular research topic which aims at matching the specific person in a multi-camera network automatically. Feature representation and metric learning…
Facial Action Unit Detection Using Attention and Relation Learning
Zhiwen Shao, Zhilei Liu, Jianfei Cai +2
Attention mechanism has recently attracted increasing attentions in the field of facial action unit (AU) detection. By finding the region of interest of each AU with the attention…
Disc-aware Ensemble Network for Glaucoma Screening from Fundus Image
Huazhu Fu, Jun Cheng, Yanwu Xu +4
Glaucoma is a chronic eye disease that leads to irreversible vision loss. Most of the existing automatic screening methods firstly segment the main structure, and subsequently calc…
Ensemble Soft-Margin Softmax Loss for Image Classification
Xiaobo Wang, Shifeng Zhang, Zhen Lei +3
Softmax loss is arguably one of the most popular losses to train CNN models for image classification. However, recent works have exposed its limitation on feature discriminability.…
Movie Question Answering: Remembering the Textual Cues for Layered Visual Contents
Bo Wang, Youjiang Xu, Yahong Han +1
Movies provide us with a mass of visual content as well as attracting stories. Existing methods have illustrated that understanding movie stories through only visual content is sti…
Simultaneous Fidelity and Regularization Learning for Image Restoration
Dongwei Ren, Wangmeng Zuo, David Zhang +2
Most existing non-blind restoration methods are based on the assumption that a precise degradation model is known. As the degradation process can only be partially known or inaccur…
Conditional Adversarial Synthesis of 3D Facial Action Units
Zhilei Liu, Guoxian Song, Jianfei Cai +2
Employing deep learning-based approaches for fine-grained facial expression analysis, such as those involving the estimation of Action Unit (AU) intensities, is difficult due to th…
Exponential Discriminative Metric Embedding in Deep Learning
Bowen Wu, Zhangling Chen, Jun Wang +1
With the remarkable success achieved by the Convolutional Neural Networks (CNNs) in object recognition recently, deep learning is being widely used in the computer vision community…
Deep Adaptive Attention for Joint Facial Action Unit Detection and Face Alignment
Zhiwen Shao, Zhilei Liu, Jianfei Cai +1
Facial action unit (AU) detection and face alignment are two highly correlated tasks since facial landmarks can provide precise AU locations to facilitate the extraction of meaning…
Review of Visual Saliency Detection with Comprehensive Information
Runmin Cong, Jianjun Lei, Huazhu Fu +3
Visual saliency detection model simulates the human visual system to perceive the scene, and has been widely used in many vision tasks. With the acquisition technology development,…
Segmentation of Drosophila Heart in Optical Coherence Microscopy Images Using Convolutional Neural Networks
Lian Duan, Xi Qin, Yuanhao He +8
Convolutional neural networks are powerful tools for image segmentation and classification. Here, we use this method to identify and mark the heart region of Drosophila at differen…
Object Detection with Mask-based Feature Encoding
Xiaochuan Fan, Hao Guo, Kang Zheng +2
Region-based Convolutional Neural Networks (R-CNNs) have achieved great success in the field of object detection. The existing R-CNNs usually divide a Region-of-Interest (ROI) into…
A CNN-based Spatial Feature Fusion Algorithm for Hyperspectral Imagery Classification
Alan J. X. Guo, Fei Zhu
The shortage of training samples remains one of the main obstacles in applying the artificial neural networks (ANN) to the hyperspectral images classification. To fuse the spatial…