Ling Zhang

I graduated from the Dept. Electrical Engineering at The City College of New York, CUNY. I have worked on unsupervised feature learning for point cloud with the Graph Convolutional Neural Netowrks under the supervision of Professor Zhigang Zhu at CCVCL Lab. I also worked on vehicle re-identification and tracking under the supervision of Professor Yingli Tian at CCNY Media Lab.

Email  /  CV  /  Github  /  Google Scholar  /  LinkedIn

we propose an unsupervised learning approach to learn features from unlabeled point cloud ”3D object” dataset by using part contrasting and object clustering with deep graph neural networks (GNNs).

we propose an unsupervised learning approach to learn features from unlabeled point cloud ”3D object” dataset by using part contrasting and object clustering with deep graph neural networks (GNNs).

Our solutions to the image-based vehicle re-identification track and multi-camera vehicle tracking track on AI City Challenge 2019 (AIC2019). Our proposed framework outperforms the current state-of-the-art vehicle ReID method by 16.3% on Veri dataset.