no code implementations • 24 Jul 2020 • Hanbin Zhao, Hao Zeng, Xin Qin, Yongjian Fu, Hui Wang, Bourahla Omar, Xi Li
As an important and challenging problem, multi-domain learning (MDL) typically seeks for a set of effective lightweight domain-specific adapter modules plugged into a common domain-agnostic network.
no code implementations • 25 Jun 2020 • Jiabao Cui, XueWei Li, Bin Li, Hanbin Zhao, Bourahla Omar, Xi Li
In this paper, we propose a novel learning scheme called epoch-evolving Gaussian Process Guided Learning (GPGL), which aims at characterizing the correlation information between the batch-level distribution and the global data distribution.
no code implementations • 9 Jun 2020 • Abdul Jabbar, Xi Li, Bourahla Omar
We survey, (I) the original GAN model and its modified classical versions, (II) detail analysis of various GAN applications in different domains, (III) detail study about the various GAN training obstacles as well as training solutions.
no code implementations • 8 Jun 2020 • Xuewei Li, Songyuan Li, Bourahla Omar, Fei Wu, Xi Li
In this paper, we see knowledge distillation in a fresh light, using the knowledge gap, or the residual, between a teacher and a student as guidance to train a much more lightweight student, called a res-student.
no code implementations • CVPR 2020 • Yifeng Chen, Guangchen Lin, Songyuan Li, Bourahla Omar, Yiming Wu, Fangfang Wang, Junyi Feng, Mingliang Xu, Xi Li
Panoptic segmentation aims to perform instance segmentation for foreground instances and semantic segmentation for background stuff simultaneously.