42 citations · 104 across the 6 of their papers we have counts for
6 papers
Gaussian Constrained Attention Network for Scene Text Recognition
Zhi Qiao, Xugong Qin, Yu Zhou +2
Scene text recognition has been a hot topic in computer vision. Recent methods adopt the attention mechanism for sequence prediction which achieve convincing results. However, we a…
Two-Level Residual Distillation based Triple Network for Incremental Object Detection
Dongbao Yang, Yu Zhou, Dayan Wu +3
Modern object detection methods based on convolutional neural network suffer from severe catastrophic forgetting in learning new classes without original data. Due to time consumpt…
Self-Training for Domain Adaptive Scene Text Detection
Yudi Chen, Wei Wang, Yu Zhou +3
Though deep learning based scene text detection has achieved great progress, well-trained detectors suffer from severe performance degradation for different domains. In general, a…
Efficient Segmentation: Learning Downsampling Near Semantic Boundaries
Dmitrii Marin, Zijian He, Peter Vajda +4
Many automated processes such as auto-piloting rely on a good semantic segmentation as a critical component. To speed up performance, it is common to downsample the input frame. Ho…
Jointly Optimize Data Augmentation and Network Training: Adversarial Data Augmentation in Human Pose Estimation
Xi Peng, Zhiqiang Tang, Fei Yang +2
Random data augmentation is a critical technique to avoid overfitting in training deep neural network models. However, data augmentation and network training are usually treated as…
Deep Poselets for Human Detection
Lubomir Bourdev, Fei Yang, Rob Fergus
We address the problem of detecting people in natural scenes using a part approach based on poselets. We propose a bootstrapping method that allows us to collect millions of weakly…