3.4k citations · 3.7k across the 22 of their papers we have counts for
4 papers · 1 filter
Deep Sampling Networks
Bolun Cai, Xiangmin Xu, Kailing Guo +2
Deep convolutional neural networks achieve excellent image up-sampling performance. However, CNN-based methods tend to restore high-resolution results highly depending on tradition…
Manifold Regularized Slow Feature Analysis for Dynamic Texture Recognition
Jie Miao, Xiangmin Xu, Xiaofen Xing +1
Dynamic textures exist in various forms, e.g., fire, smoke, and traffic jams, but recognizing dynamic texture is challenging due to the complex temporal variations. In this paper,…
Single Image Super-Resolution Using Multi-Scale Convolutional Neural Network
Xiaoyi Jia, Xiangmin Xu, Bolun Cai +1
Methods based on convolutional neural network (CNN) have demonstrated tremendous improvements on single image super-resolution. However, the previous methods mainly restore images…
Multi-scale Convolutional Neural Networks for Crowd Counting
Lingke Zeng, Xiangmin Xu, Bolun Cai +2
Crowd counting on static images is a challenging problem due to scale variations. Recently deep neural networks have been shown to be effective in this task. However, existing neur…