913 citations · 4.5k across the 87 of their papers we have counts for
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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…
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…
Learning Deep Representation for Face Alignment with Auxiliary Attributes
Zhanpeng Zhang, Ping Luo, Chen Change Loy +1
In this study, we show that landmark detection or face alignment task is not a single and independent problem. Instead, its robustness can be greatly improved with auxiliary inform…
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…