activity
20172020
most citedDeep Ranking Model by Large Adaptive Margin Learning for Person Re-identification

43 citations · 85 across the 7 of their papers we have counts for

collaborators

8 papers

cs.CV20201 cited

Teacher-Student Asynchronous Learning with Multi-Source Consistency for Facial Landmark Detection

Rongye Meng, Sanping Zhou, Xingyu Wan +2

Due to the high annotation cost of large-scale facial landmark detection tasks in videos, a semi-supervised paradigm that uses self-training for mining high-quality pseudo-labels t…

cs.CV2020

End-to-End Multi-Object Tracking with Global Response Map

Xingyu Wan, Jiakai Cao, Sanping Zhou +1

Most existing Multi-Object Tracking (MOT) approaches follow the Tracking-by-Detection paradigm and the data association framework where objects are firstly detected and then associ…

cs.CV20201 cited

Meta Corrupted Pixels Mining for Medical Image Segmentation

Jixin Wang, Sanping Zhou, Chaowei Fang +2

Deep neural networks have achieved satisfactory performance in piles of medical image analysis tasks. However the training of deep neural network requires a large amount of samples…

cs.CV202029 cited

Multiple Object Tracking by Flowing and Fusing

Jimuyang Zhang, Sanping Zhou, Xin Chang +4

Most of Multiple Object Tracking (MOT) approaches compute individual target features for two subtasks: estimating target-wise motions and conducting pair-wise Re-Identification (Re…

cs.CV201911 cited

Frame-wise Motion and Appearance for Real-time Multiple Object Tracking

Jimuyang Zhang, Sanping Zhou, Jinjun Wang +1

The main challenge of Multiple Object Tracking (MOT) is the efficiency in associating indefinite number of objects between video frames. Standard motion estimators used in tracking…

cs.CV2019

SE2Net: Siamese Edge-Enhancement Network for Salient Object Detection

Sanping Zhou, Jimuyang Zhang, Jinjun Wang +2

Deep convolutional neural network significantly boosted the capability of salient object detection in handling large variations of scenes and object appearances. However, convoluti…