Research Team of Prof. Wu Xiao Publishes Papers at International Conferences

Source:SIST  Author:Hu Xiaoyang  Date:2017-07-03  Click:404

Prof. Wu Xiao’s research team of virtual reality and multimedia publishes one paper at the ACM International Conference on Multimedia (ACM MM) and two papers at the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) after the successful publishing of an Oral in the previous year. The paper published at the ACM MM is selected as an Oral. Among 675 submissions, only 50 of them are selected as Orals, contributing to an acceptance rate of 7.5%. The institution indicated by the main authors of the preceding papers is SWJTU. This is the 10th paper concerning artificial intelligence published by Prof. Wu’s team in top publications and at top conferences.

Prof. Wu’s team applies deep learning algorithms to e-Commerce and fashion search, which is of academic and commercial values and a breakthrough in advanced pattern recognition and artificial intelligence. The papers are key research achievements of SIST, as well as progress made by SIST in computer science.

Sketch Recognition with Deep Visual-Sequential Fusion Model, authored by PhD candidate He Junyan and jointly completed by Prof. Wu Xiao of SWJTU and Prof. Jiang Yugang of Fudan University, is selected as an Oral by ACM MM.

Memory-Augmented Attribute Manipulation Networks for Interactive Fashion Search, authored by PhD candidate Zhao Bo and jointly completed by Prof. Wu Xiao of SWJTU and Prof. Feng Jiashi of University of Singapore, is accepted by CVPR.

Video2Shop: Exact Matching Clothes in Videos to Online Shopping Images, authored by PhD candidate Cheng Zhiqi and jointly completed by Prof. Wu Xiao of SWJTU, and senior researcher Hua Xiansheng and advanced algorithm expert Liu Yang of iDST, is accepted by CVPR.

The virtual reality and multimedia research team is committed to advanced research covering video coding technique, multimedia big data, artificial intelligence, machine learning, virtual reality, and digital railway. The team is involved in more than 20 national, ministerial, and provincial research projects and cooperates with multiple railway and local organizations.