Wenhan Luo

Email  /  Google Scholar  /  Publication  /  Code  /  Links

I am an applied research scientist at Tencent, where I work on solving real-world problems using computer vision and machine learning techniques. Prior to Tencent, I worked for Amazon (A9) in Palo Alto, California, where I developed deep models for better visual search experience. Before that, I worked as a research scientist in Tencent AI Lab. The techniques I have developed/involved have been shipped to several products in Tencent such as WeChat and myapp. I received the Ph.D. degree from Imperial College London, UK, 2016, M.E. degree from Institute of Automation, Chinese Academy of Sciences, China, 2012 and B.E. degree from Huazhong University of Science and Technology, China, 2009. [CV]



Research

I am interested in several topics in computer vision and machine learning, such as motion analysis (especially object tracking), image/video quality restoration, object detection and recognition, reinforcement learning.



News

2021/05 - Our work of active visual tracking is accepted by ICML2021.

2021/05 - One paper of image dehazing to appear in IEEE Transactions on Image Processing.

2021/04 - Our work of human image synthesis is accepted to appear in TPAMI.

2021/03 - One paper to appear in IEEE Transactions on Geoscience and Remote Sensing.

2021/02 - One paper to appear in IEEE Transactions on Multimedia.

2020/12 - The paper "Multiple Object Tracking: A Literature Review" is accepted by Artificial Intelligence.

2020/12 - Invited to serve as a Senior PC member for IJCAI 2021.

2020/11 - One paper of pedestrian detection to appear in IEEE Transactions on Image Processing.

2020/09 - An invited talk is given in SUSTech, hosted by Prof. Xiaoying Tang.

2020/09 - One paper of optical flow estimation to appear in IEEE Transactions on Image Processing.

2020/07 - One paper to appear in ACM MM 2020 (Oral).

2020/07 - One paper to appear in ECCV2020.

2020/06 - One paper of multiple object tracking to appear in Pattern Recognition.



Recent Projects

Fine-grained Image-to-Image Transformation towards Visual Recognition,
W. Xiong, Y. He, Y. Zhang, W. Luo, L. Ma, J. Luo,
Proc. of IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), USA, 2020.

Image-to-image translation with fine-grained category towards maintaining identity information.


Liquid Warping GAN: A Unified Framework for Human Motion Imitation, Appearance Transfer and Novel View Synthesis,
W. Liu+, Z. Piao, J. Min, W. Luo, L. Ma, S. Gao,
Proc. of International Conference on Computer Vision (ICCV), Korea, 2019.

A unified framework for human motion transfer, appearance transfer and novel view synthesis using GAN.


End-to-end Active Object Tracking via Reinforcement Learning,
W. Luo*, P. Sun*, F. Zhong, W. Liu, T. Zhang and Y. Wang,
International Conference on Machine Learning (ICML), Sweden, 2018.

The first work proposing the active visual tracking problem and addressing it with reinforcement learning.


Learning to Generate Time-Lapse Videos Using Multi-Stage Dynamic Generative Adversarial Networks,
W. Xiong+, W. Luo, L. Ma, W. Liu and J. Luo,
Proc. of IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), USA, 2018.

A multi-stage GAN framework to generate time-lapse video given a single image.



I like this website           Design credit