970 citations · 2.8k across the 29 of their papers we have counts for
3 papers · 1 filter
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…
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…