activity
20102017
most citedSingle-Shot Refinement Neural Network for Object Detection

112 citations · 211 across the 6 of their papers we have counts for

collaborators

8 papers

cs.CV2017112 cited

Single-Shot Refinement Neural Network for Object Detection

Shifeng Zhang, Longyin Wen, Xiao Bian +2

For object detection, the two-stage approach (e.g., Faster R-CNN) has been achieving the highest accuracy, whereas the one-stage approach (e.g., SSD) has the advantage of high effi…

cs.CV201733 cited

SFD: Single Shot Scale-invariant Face Detector

Shifeng Zhang, Xiangyu Zhu, Zhen Lei +3

This paper presents a real-time face detector, named Single Shot Scale-invariant Face Detector (SFD), which performs superiorly on various scales of faces with a single deep ne…

cs.CV20172 cited

Learning Efficient Image Representation for Person Re-Identification

Yang Yang, Shengcai Liao, Zhen Lei +1

Color names based image representation is successfully used in person re-identification, due to the advantages of being compact, intuitively understandable as well as being robust…

cs.CV2016

Learning Discriminative Features with Class Encoder

Hailin Shi, Xiangyu Zhu, Zhen Lei +2

Deep neural networks usually benefit from unsupervised pre-training, e.g. auto-encoders. However, the classifier further needs supervised fine-tuning methods for good discriminatio…

cs.CV2016

CRAFT Objects from Images

Bin Yang, Junjie Yan, Zhen Lei +1

Object detection is a fundamental problem in image understanding. One popular solution is the R-CNN framework and its fast versions. They decompose the object detection problem int…

cs.CV201539 cited

When Face Recognition Meets with Deep Learning: an Evaluation of Convolutional Neural Networks for Face Recognition

Guosheng Hu, Yongxin Yang, Dong Yi +4

Deep learning, in particular Convolutional Neural Network (CNN), has achieved promising results in face recognition recently. However, it remains an open question: why CNNs work we…