50 citations · 213 across the 25 of their papers we have counts for
7 papers · 1 filter
Deep Tiny Network for Recognition-Oriented Face Image Quality Assessment
Baoyun Peng, Min Liu, Zhaoning Zhang +2
Face recognition has made significant progress in recent years due to deep convolutional neural networks (CNN). In many face recognition (FR) scenarios, face images are acquired fr…
Towards Precise End-to-end Weakly Supervised Object Detection Network
Ke Yang, Dongsheng Li, Yong Dou
It is challenging for weakly supervised object detection network to precisely predict the positions of the objects, since there are no instance-level category annotations. Most exi…
Correlation Congruence for Knowledge Distillation
Baoyun Peng, Xiao Jin, Jiaheng Liu +5
Most teacher-student frameworks based on knowledge distillation (KD) depend on a strong congruent constraint on instance level. However, they usually ignore the correlation between…
Exploring Frame Segmentation Networks for Temporal Action Localization
Ke Yang, Xiaolong Shen, Peng Qiao +3
Temporal action localization is an important task of computer vision. Though many methods have been proposed, it still remains an open question how to predict the temporal location…
Loss Rank Mining: A General Hard Example Mining Method for Real-time Detectors
Hao Yu, Zhaoning Zhang, Zheng Qin +4
Modern object detectors usually suffer from low accuracy issues, as foregrounds always drown in tons of backgrounds and become hard examples during training. Compared with those pr…
Diagonalwise Refactorization: An Efficient Training Method for Depthwise Convolutions
Zheng Qin, Zhaoning Zhang, Dongsheng Li +2
Depthwise convolutions provide significant performance benefits owing to the reduction in both parameters and mult-adds. However, training depthwise convolution layers with GPUs is…
S-OHEM: Stratified Online Hard Example Mining for Object Detection
Minne Li, Zhaoning Zhang, Hao Yu +2
One of the major challenges in object detection is to propose detectors with highly accurate localization of objects. The online sampling of high-loss region proposals (hard exampl…