Junru Wu

Ph.D. Student

Dept. of Computer Science & Enigneering, Texas A&M University

sandboxmaster@tamu.edu

[Google Scholar] [Linkedln] [CV]

Brief Biography

I’m a third year Ph.D Student in Computer Science at Texas A&M University, my advisor is Dr. Zhangyang Wang. From 2016 - 2017, I was a research assistant working with Dr. Shenghua Gao at Visual Computing Lab, ShanghaiTech University. I received my B.Eng degree in Electrical Engineering from Tongji University, Shanghai in 2016.

Work Experience

Research Interests

My research interests lie in computer vision and machine learning, specifically in the following topics
(a) Efficient Neural Architecture Search
(b) Fast & Accurate image/video deblurring, denosing
(c) Neural Newtwork Compression/Acceleration, Energy efficient Neural Networks
(d) Saliency Detecion in VR, Personalized Saliency Detecion

Publication

Junru Wu, Xiang Yu, Ding Liu, Manmohan Chandraker, Zhangyang Wang. “DAVID: Dual-Attentional Video Deblurring” Winter Conference on Applications of Computer Vision (WACV), 2020. [PDF]

Orest Kupyn, Tetiana Martyniuk, Junru Wu, Zhangyang Wang. “DeblurGAN-v2: Deblurring (Orders-of-Magnitude) Faster and Better” The International Conference on Computer Vision (ICCV), 2019. [PDF] [Github]

Sicheng Wang, Bihan Wen, Junru Wu, Dacheng Tao and Zhangyang Wang. “Segmentation-Aware Image Denoising without Knowing True Segmentation” Submitted to TIP. [PDF] [Github]

Rosaura G. VidalMata*, …, Junru Wu, …, Walter J. Scheirer. “Bridging the gap between computational photography and visual recognition” IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020. [PDF] [Github]

Junru Wu, Yue Wang, Zhenyu Wu, Zhangyang Wang, Ashok Veeraraghavan and Yingyan Lin. “Deep k-Means: Re-Training and Parameter Sharing with Harder Cluster Assignments for Compressing Deep Convolutions” International Conference on Machine Learning (ICML), 2018. [PDF] [Github]

Yanyu Xu, Yanbing Dong, Junru Wu, Zhengzhong Sun, Zhiru Shi, Jingyi Yu, and Shenghua Gao. “Gaze Prediction in Dynamic 360◦ Immersive Videos” IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2018. [PDF] [Github]

Yanyu Xu *, Shenghua Gao *, Junru Wu*, Nianyi Li and Jingyi Yu, “Personalized Saliency and Its Prediction” IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2018. [PDF]. *Equal contributions

Yanyu Xu, Nianyi Li, Junru Wu, Jingyi Yu, and Shenghua Gao. “Beyond Universal Saliency: Personalized Saliency Prediction with Multi-task CNN” IEEE International Joint Conference on Artificial Intelligence (IJCAI), 2017. (Best Student Paper Finalist) [PDF] [Github]

** Cartoon portrait credit to Shuai Yang