1.8k citations · 8.6k across the 108 of their papers we have counts for
11 papers · 2 filters
Highly Efficient Forward and Backward Propagation of Convolutional Neural Networks for Pixelwise Classification
Hongsheng Li, Rui Zhao, Xiaogang Wang
We present highly efficient algorithms for performing forward and backward propagation of Convolutional Neural Network (CNN) for pixelwise classification on images. For pixelwise c…
Person Re-identification by Saliency Learning
Rui Zhao, Wanli Ouyang, Xiaogang Wang
Human eyes can recognize person identities based on small salient regions, i.e. human saliency is distinctive and reliable in pedestrian matching across disjoint camera views. Howe…
Deeply learned face representations are sparse, selective, and robust
Yi Sun, Xiaogang Wang, Xiaoou Tang
This paper designs a high-performance deep convolutional network (DeepID2+) for face recognition. It is learned with the identification-verification supervisory signal. By increasi…
DeepID-Net: Deformable Deep Convolutional Neural Networks for Object Detection
Wanli Ouyang, Xiaogang Wang, Xingyu Zeng +8
In this paper, we propose deformable deep convolutional neural networks for generic object detection. This new deep learning object detection framework has innovations in multiple…
Pedestrian Detection aided by Deep Learning Semantic Tasks
Yonglong Tian, Ping Luo, Xiaogang Wang +1
Deep learning methods have achieved great success in pedestrian detection, owing to its ability to learn features from raw pixels. However, they mainly capture middle-level represe…
Fully Convolutional Neural Networks for Crowd Segmentation
Kai Kang, Xiaogang Wang
In this paper, we propose a fast fully convolutional neural network (FCNN) for crowd segmentation. By replacing the fully connected layers in CNN with 1 by 1 convolution kernels, F…
Deep Learning Face Attributes in the Wild
Ziwei Liu, Ping Luo, Xiaogang Wang +1
Predicting face attributes in the wild is challenging due to complex face variations. We propose a novel deep learning framework for attribute prediction in the wild. It cascades t…
DeepID-Net: multi-stage and deformable deep convolutional neural networks for object detection
Wanli Ouyang, Ping Luo, Xingyu Zeng +12
In this paper, we propose multi-stage and deformable deep convolutional neural networks for object detection. This new deep learning object detection diagram has innovations in mul…
Deep Learning Multi-View Representation for Face Recognition
Zhenyao Zhu, Ping Luo, Xiaogang Wang +1
Various factors, such as identities, views (poses), and illuminations, are coupled in face images. Disentangling the identity and view representations is a major challenge in face…
Deep Learning Face Representation by Joint Identification-Verification
Yi Sun, Xiaogang Wang, Xiaoou Tang
The key challenge of face recognition is to develop effective feature representations for reducing intra-personal variations while enlarging inter-personal differences. In this pap…
Recover Canonical-View Faces in the Wild with Deep Neural Networks
Zhenyao Zhu, Ping Luo, Xiaogang Wang +1
Face images in the wild undergo large intra-personal variations, such as poses, illuminations, occlusions, and low resolutions, which cause great challenges to face-related applica…