J
Junru Wu
Researcher at Texas A&M University
Publications - 19
Citations - 1161
Junru Wu is an academic researcher from Texas A&M University. The author has contributed to research in topics: Computer science & Salience (neuroscience). The author has an hindex of 10, co-authored 16 publications receiving 607 citations. Previous affiliations of Junru Wu include ShanghaiTech University.
Papers
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Proceedings ArticleDOI
DeblurGAN-v2: Deblurring (Orders-of-Magnitude) Faster and Better
TL;DR: It is demonstrated that DeblurGAN-V2 has very competitive performance on several popular benchmarks, in terms of deblurring quality (both objective and subjective), as well as efficiency, and is effective for general image restoration tasks too.
Proceedings ArticleDOI
Gaze Prediction in Dynamic 360° Immersive Videos
TL;DR: This paper presents the large-scale eye-tracking in dynamic VR scene dataset, and proposes to compute saliency maps at different spatial scales: the sub-image patch centered at current gaze point, theSub-image corresponding to the Field of View (FoV), and the panorama image.
Posted Content
DeblurGAN-v2: Deblurring (Orders-of-Magnitude) Faster and Better
TL;DR: DeblurGAN-v2 as mentioned in this paper is based on a relativistic conditional GAN with a double-scale discriminator and introduces the Feature Pyramid Network into deblurring, as a core building block in the generator.
Posted Content
Deep $k$-Means: Re-Training and Parameter Sharing with Harder Cluster Assignments for Compressing Deep Convolutions
TL;DR: Deep $k$-means clustering as discussed by the authors proposes a simple yet effective scheme for compressing convolutions through weight-sharing, by only recording $K$ cluster centers and weight assignment indexes.
Journal ArticleDOI
Bridging the Gap Between Computational Photography and Visual Recognition
Rosaura G. VidalMata,Sreya Banerjee,Brandon RichardWebster,Michael Albright,Pedro Davalos,Scott McCloskey,Ben Miller,Asong Tambo,Sushobhan Ghosh,Sudarshan Nagesh,Ye Yuan,Yueyu Hu,Junru Wu,Wenhan Yang,Xiaoshuai Zhang,Jiaying Liu,Zhangyang Wang,Hwann-Tzong Chen,Tzu-Wei Huang,Wen-Chi Chin,Yi-Chun Li,Mahmoud Lababidi,Charles Otto,Walter J. Scheirer +23 more
TL;DR: Six new algorithms for image restoration or enhancement, created as part of the IARPA sponsored UG, are introduced, including a novel psychophysics-based evaluation regime for human assessment and a realistic set of quantitative measures for object recognition performance.